Representatives of the American Diabetes Association (Stewart Perry, Tom Boyer, Using State-level data on diabetes care from the 2003 National Healthcare …

Diabetes Care Quality Improvement:
A Resource Guide for State Action

Prepared for:
Agency for Healthcare Research and Quality
US Department of Health and Human Services
540 Gaither Road
Rockville, Maryland 20850
wwwahrqgov

Contract No 290-00-0004
The Medstat Group, Inc
The Council of State Governments

Prepared by:
Rosanna M Coffey, PhD
Trudi L Matthews, MA
Kelly McDermott, MA

AHRQ Publication No 04-0072
September 2004
Acknowledgments

This Resource Guide was prepared for the Agency for Healthcare Research
Quality AHRQ by Rosanna M Coffey, PhD, and Kelly McDermott, MA, The
Medstat Group, Inc, and Trudi L Matthews, MA, The Council of State
Governments The idea for the Resource Guide belongs to Denise Remus,
PhD, RN and other AHRQ staff who strive to move research into the
practice of health care and health care policy Dwight McNeil, PhD, AHRQ
Task Leader, and Edward Kelley, PhD, Director of the National Healthcare
Quality Report, guided this work and set the standard for its quality
Numerous people contributed to the concept by sharing information, serving
on focus groups, and
reading multiple drafts We acknowledge the generous
consultations and contributions of:
Four Partners in the Healthcare Cost and Utilization Project from both
State hospital associations and State government agencies Vi Naylor,
Georgia Hospital Association; Jerry OKeefe, Massachusetts Division of
Health Care Finance and Policy and Department of Public Health; Mark
Sonneborn, Michigan Health and Hospital Association; and Gary Blair,
Washington State Department of Health
Members of the Council of State Governments, who served as focus group
members Representative Mary Skinner, Washington; Representative Greg
Jolivette, Ohio; Kurt Knickrehm, Director, Arkansas Department of Human
Services; Assemblyman Felix Ortiz, New York; Senator Linda Higgins,
Minnesota; Jan Norman, Manager, Diabetes Control Program, Washington
State Department of Health; Senator Larry Salmans, Kansas
Centers for Disease Control and Prevention, Division of Diabetes
Translation staff who provided suggestions and important insights on
quality improvement activities of the States and the CDC Frank Vinicor,
Michael Engelgau, Russell Sniegowski, and David Guthrie
Centers
for Disease Control and Prevention staff who provided comments on
a prior draft
Representatives of the American Diabetes Association Stewart Perry, Tom
Boyer, Nathaniel Clark, MD, and Ann Albright, PhD, RD
State and Federal officials who provided personal stories, program
background and other information Governor Mike Huckabee, Arkansas;
Representative Dan Bosley, Massachusetts; Representative Fran Wendelboe,
New Hampshire; Dr Kimberlydawn Wisdom, Surgeon General of the State of
Michigan; Martha Roberts and Laurel Reger of the Minnesota Diabetes
Prevention and Control Program DPCP; Jo Anderson of the Missouri DPCP;
Janet Reese of the North Carolina DPCP; Dr Lawrence Harkless, Chairman
of the Texas Diabetes Council; Pat Zapp of the Wisconsin DPCP
Sally Sue Brown, formerly of The Council of State Governments, who
provided research assistance for the Resource Guide
____________________________________________________________________________
__
This document is in the public domain and may be used and reprinted without
permission except for any copyrighted materials noted for which further
reproduction is prohibited without the specific permission of
copyright
holders AHRQ appreciates citation as to source, and the suggested format
is provided below:
Coffey RM, Matthews TL, McDermott K Diabetes Care Quality Improvement: A
Resource Guide for State Action Prepared by The Medstat Group, Inc and
The Council of State Governments under Contract No 290-00-0004
Rockville, MD: Agency for Healthcare Research and Quality, Department of
Health and Human Services; September 2004 AHRQ Pub No 04-0072
Foreword

Diabetes Care Quality Improvement: A Resource Guide for State Action and
its accompanying Workbook were developed by the Agency for Healthcare
Research and Quality AHRQ as learning tools for all State officials who
want to improve the quality of health care Using State-level data on
diabetes care from the 2003 National Healthcare Quality Report, this
Resource Guide is designed to help States assess the quality of care in
their States and fashion quality improvement strategies suited to State
conditions The States mentioned in this Resource Guide gave permission to
use their data for illustrative and comparative purposes so that others
could learn by their examples

Many people for whom these learning tools were intended-State elected
and
appointed leaders as well as officials in State health departments,
Diabetes Prevention and Control Programs, Medicaid offices, and elsewhere-
provided comments and feedback throughout the development and finalization
process From this process, we learned that they intend to use the
Resource Guide and Workbook in many different ways: to assess their
current structure and status, to create new quality improvement programs,
to build upon existing programs, as an orientation for new staff, and to
share with their partners such as the American Diabetes Association

The Resource Guide and Workbook can serve as a meeting place, where the
creative minds of those who struggle with quality improvement can share
their expertise, ideas, knowledge, and solutions The various modules are
intended for different users Senior leaders are responsible for making
the case for diabetes quality improvement and taking action Modules 1, 4,
and 6 while program staff would need to provide the information necessary
to develop and implement a quality improvement strategy Modules 2, 3, and
5 The goal, of course, is that all groups of people work on these
modules as a team It is within those
discussions and sharing and working
together that we hope to achieve what we set out to do-help States improve
the quality of diabetes care

If you have any comments or questions on the Resource Guide or Workbook,
please contact AHRQs Center for Quality Improvement and Patient Safety,
540 Gaither Road, Suite 3000, Rockville, MD 20850

Contents

Executive Summary v
Introduction: How and Why To Use This Resource Guide 1
Purpose of the Resource Guide 2
Audiences for the Resource Guide 3
Structure and Organization of the Resource Guide 3
Module 1: Background - Making the Case for Diabetes Care Quality
Improvement 7
The Importance of Diabetes 8
The NHQR and NHDR as Resources for State Leaders 15
The Quality Improvement Opportunity 18
Module 2: Data - Understanding the Foundation of Quality Improvement
21
Quality Measurement 22
Sources of NHQR Data on Diabetes Care 25
Module 3: Information - Interpreting State Estimates of Diabetes Quality
41
Deriving Information From Data 42
Step 1: Identifying Appropriate Metrics and Comparisons 43
Step 2: Interpreting the Data: What Does It Mean? 54
Module 4: Action - Learning From Activities
Currently Underway 61
Selected Public/Private Quality Improvement Initiatives 62
Selected Federal Programs and Resources for Diabetes Care Quality
Improvement 65
State Approaches to Diabetes Care Quality Improvement 69
Selected Local Quality Improvement Efforts 82
Module 5: Improvement - Developing a Strategy for Diabetes Quality
Improvement 85
A Model for Quality Improvement 86
Developing a State Strategy For Improving Diabetes Care Quality 90
Integrating Quality Improvement Activities Across Conditions 92
The Importance of Evaluation 93
Module 6: The Way Forward - Promoting Quality Improvement in the States
99
What Can State Leaders Contribute to Quality Improvement? 99
References 102
Appendixes:
A Acronyms Used in This Resource Guide 109
B List of NHQR Data Sources, Including Those Supporting State
Estimates 111
C Additional Data Resources Related to Diabetes Care Quality
112
D Benchmarks From the NHQR 127

E Information on Statistical Significance 131

F NHQR Quality Measures for All Conditions by State 134

G Index of Diabetes Quality Improvement Initiatives
148

H CDC Funding for States Diabetes Programs, 2003-2004 152

Executive Summary

As rates of diabetes increase across the country, roughly tracking with
increases in obesity rates, States are quickly approaching a time when
budgets will not be able to withstand the pressure of treating the flood
of obesity-related diseases Consequently, while we search for better
and more efficient ways of treating diabetes and helping people manage
the disease so that costly procedures can be prevented, we must find more
ways to create incentives for people to make healthy lifestyle choices
The State that figures out how to do this, while respecting and
protecting individual liberties, will be the model for the Nation

- An Interview with Governor Mike Huckabee, Arkansas

Health care analysts and researchers have documented extensive gaps between
the care that patients receive and what the medical community has
determined to be the most effective care Despite unrivaled technological
innovation in American health care, too much of the care that is delivered
to patients does not meet the accepted standards of quality More
alarming,
abundant research has demonstrated that these gaps in quality are
responsible for wasteful, ineffective care, preventable medical
complications, avoidable hospitalizations, decreased quality of life,
disability, and premature death

In an era of rising alarm over the cost of health care, it is bewildering
that so much of the health care that Americans pay for does not meet
accepted standards of quality When considered in light of the number of
preventable deaths and greater disability due to poor quality care, it is
intolerable A growing number of health care analysts and leaders argue
that the Nation simply cannot afford to ignore the widespread quality
problems that exist in US health care system

As the lead Federal agency supporting research into the quality, cost
effectiveness, and safety of health care, the Agency for Healthcare
Research and Quality AHRQ is at the forefront of equipping health care
professionals, policymakers and leaders with the information they need to
address the health care quality gap The National Healthcare Quality Report
NHQR, the National Healthcare Disparities Report NHDR, and this
Diabetes Care Quality Improvement: A Resource Guide for State
Action are
new tools to meet the challenge of improving the quality of care in
America

The National Healthcare Quality Report National Healthcare Disparities
Report

In 2003, AHRQ released the first ever National Healthcare Quality Report
and National Healthcare Disparities Report These reports, mandated by
Congress, collected and analyzed national and State-level data from a
variety of reliable sources to measure the state of health care quality and
health disparities in the Nation

The data in the NHQR and NHDR demonstrate that the gap between health care
research and practice is not just an occasional occurrence but is pervasive
throughout health care It affects all patient groups, even those with the
most common medical conditions, and every State The NHQR and NHDR provide
further confirmation that, while in some areas care is improving, the
health care system in America has a long way to go before it delivers care
that is consistent with accepted guidelines and does not vary significantly
by geography, race, ethnicity or socioeconomic status

Both reports also called for health policy leaders and health care
professionals to consider ways to improve the quality of care
in the United
States and take action to deal with the persistent and costly gaps in
health care quality Ultimately, quality improvement occurs at the front
lines of health care - health care professionals and clients enhancing
their understanding and changing their actions to align with what evidence
has revealed as effective care State leaders can be catalysts for this
change

States as Key Contributors to Quality Improvement

A number of sources have pointed to States as key contributors to improving
the quality of care in America In two reports, Crossing the Quality
Chasm: A New Health Care System for the 21st Century and Fostering Rapid
Advances in Health Care: Learning from System Demonstrations, the Institute
of Medicine IOM, 2001a and 2002 outlined a variety of strategies to
advance public policy around quality improvement, including attention to
care for chronic diseases The reports emphasized the role of States along
with the Federal Government in quality improvement Secretary of Health
and Human Services Tommy G Thompson has stated that State-level
demonstrations are needed to test a variety of quality improvement
approaches, evaluate the effectiveness of different
models, and inform
national efforts IOM, 2003a

There is a great deal that State leaders can do to support and encourage
quality improvement, and thereby, to improve health outcomes, reduce the
burden of disease, and increase the efficiency of the health care system
As large health care purchasers, guardians of public health and health care
innovators, States can champion quality improvement and institute best
practices that can transform health care systems A number of States have
already undertaken ambitious quality improvement plans, collecting their
own data, and developing and implementing clinical guidelines to help
improve quality The scarcity of reliable data and quality improvement
tools suited to the State context have made quality improvement in some
cases a complex undertaking for pioneering States

The Role of This Resource Guide

AHRQ has published this Resource Guide to assist States with quality
improvement efforts As the NHQR and the IOM reports make clear, chronic
diseases present unique quality challenges but also have potential for
great improvements in care Thus, this Resource Guide focuses on diabetes,
one of the conditions highlighted in the NHQR Using
State-level data on
diabetes care from the NHQR, this Resource Guide is designed to help States
assess the quality of care in their States and fashion quality improvement
strategies suited to State conditions AHRQ hopes to catalyze and equip
State health care leaders-governors, State legislators, agency officials,
and staff, as well as nongovernmental leaders at the State level such as
professional associations, business groups, community organizations and
others-to take action to improve the quality of health care in America

AHRQ, other Federal agencies, national organizations, States, and others
have developed a variety of resources that can assist State leaders in
enhancing their quality improvement efforts These resources include
clinical research and guidelines for care, measures and data to assess care
quality and document improvements over time, and proven policy strategies
to improve health care quality Diabetes is an especially important target
for quality improvement efforts because of the current high cost and rate
of preventable complications from diabetes, the widely accepted guidelines
for care and data measures for tracking improvements in diabetes care, and
the
variety of promising quality improvement approaches from State diabetes
prevention and control programs and other diabetes initiatives

Resource Guide Overview

This Resource Guide provides a wealth of information and points to
excellent resources to help States develop quality improvement strategies
The Resource Guide is divided into six modules Each deals with a
particular component of the quality improvement process Because officials
in different parts of State government have different roles in quality
improvement, this guide is designed to meet the unique information needs of
a variety of State leaders Knowing how it is organized, State leaders can
review and use the sections that are most relevant and appropriate for
them

Module 1: Background - Making the Case for Diabetes Care Quality
Improvement provides an overview of diabetes and quality improvement It
helps to answer the question of why States should care about these
issues State leaders should care because of the following:

o Increasing prevalence of diabetes and its link to obesity

o Seriousness of diabetes complications and their effect on quality of
life and productivity

o
High health care cost of diabetes complications

o Problems with health care disparities for different groups

o Proven effectiveness of interventions to prevent type 2 diabetes and
delay complications for all types of diabetes

o Potential for a significant return from investments in improving
diabetes quality of care

o Significant gaps in quality that exist for diabetes care

o Opportunity for States to develop quality improvement strategies and
document improvements in diabetes care through use of data from the
NHQR and this guide

Module 2: Data - Understanding the Foundation of Quality Improvement
looks at the importance of data collection in assessing quality and the
role of quality measurement This module will assist State officials by
providing:

o A listing and explanation of a variety of quality measures from the
NHQR and NHDR on diabetes care

o Data tables and maps that State leaders can use to assess the quality
of care in their States

o Guidance on selecting reliable measures, collecting good data, and the
inherent limitations of data sources

o Estimates for all 50
States on the direct and indirect costs of
diabetes and on the medical care costs related to diabetes for
Medicaid

Module 3: Information - Interpreting State Estimates of Diabetes Quality
takes the next step in the quality improvement process by showing State
leaders how to turn data into information to answer key questions that
should be understood before action is taken This module examines:

o Different benchmarks that States can use to assess their States
performance in providing quality diabetes care

o NHQR data from different States-Georgia, Massachusetts, Michigan and
Washington-that provide State leaders with concrete examples of how
one can draw conclusions from the data

o Various factors that affect health care outcomes and the delivery of
quality care-including socioeconomic factors, biological and
behavioral differences, and health system characteristics-and the role
these factors play in assessments of health care quality in the
States

Module 4: Action - Learning From Activities Currently Underway provides
State leaders with a variety of national, public-private, Federal, State

and local resources and best practices in diabetes quality improvement
that can inform State efforts The module provides:

o Overviews of programs on national diabetes measures, chronic care
improvement, and disease and self-management

o Overviews of the Federal programs that partner and provide funding for
diabetes quality improvement efforts in the States

o A catalog of State diabetes quality improvement approaches in
partnership/planning activities, program development, and
dissemination, with examples from a variety of States

o More extensive profiles of diabetes quality improvement approaches in
California, Michigan, Missouri, and North Carolina

o A worksheet for analyzing current diabetes quality improvement
activity in a State

Module 5: Improvement - Developing a Strategy for Diabetes Quality
Improvement provides models and tools for State leaders to use in
crafting a quality improvement strategy for a given State The module
examines the Plan-Do-Study-Act PDSA model, which is used frequently in
quality improvement in clinical settings, and adapts that model to State
policymaking Some of
the tools and issues covered in this module
include:

o The application of the PDSA model to one State program-the Wisconsin
Collaborative Diabetes Quality Improvement Project

o A worksheet for assembling and analyzing State-specific data about
diabetes and health care quality

o A PDSA model checklist of steps for designing a State quality
improvement strategy that fits with and builds upon current State
activities

o Discussion of the appropriate scope of State quality improvement
efforts, either focused on diabetes alone or on diabetes in connection
with other health care conditions

o An overview of the importance of evaluation

Module 6: The Way Forward - Promoting Quality Improvement in the States
concludes the Resource Guide and examines the opportunities for States to
contribute to improving diabetes care quality, including:

o Providing leadership and shared vision to inspire others to become
involved in improving health care quality

o Fostering partnerships and collaborations between key parties, such as
health care professionals, providers, patients, purchasers, as well as

elected and appointed State government leaders and State government
experts on diabetes

o Fostering planning and setting goals that includes specific steps and
deliverables so that partners move together

o Enhancing measurement and reporting to identify the most troublesome
areas and prioritize resources and attention to those areas that most
need improvement

o Improving the infrastructure of health care quality through attention
to professional education, data systems, financing and delivery
systems, research, and patient education resources, among others

o Including evaluation and accountability to track how well or poorly a
quality improvement intervention is working and the health care system
is performing

o Creating incentives to reward the delivery of high quality care

This Resource Guide is designed to demonstrate for State leaders the need
for quality improvement in diabetes It also provides data, information,
best practices and quality improvement tools that can assist State leaders
in crafting diabetes quality improvement strategies

Much has already been done by States, but data from the
NHQR show us that
much remains to be done to achieve quality care for all people with
diabetes By reviewing and analyzing this Resource Guide, assessing the
local context, and designing a diabetes quality improvement strategy, State
leaders can identify opportunities to make a difference in the quality of
care their constituents receive The experiences of States that have
implemented quality improvement for diabetes care provide valuable insights
into what can be accomplished through innovative, visionary efforts by
State leaders
Introduction: How and Why To Use This Resource Guide

Three and one-half years ago while waiting in an examining room during a
routine doctors visit, Representative Dan Bosley of Massachusetts was
reading a poster on the wall of the doctors office As he read the
poster, a strange thing occurred He recognized some remarkable
similarities between the disease described in the poster and some
symptoms he was experiencing When his doctor came in to do the exam,
Rep Bosley mentioned that he had the symptoms described in the poster
His doctor laughed and said that those symptoms could be warning signs
for a lot of things
Fortunately, the doctor performed a blood test
That is how Rep Bosley found out he had type 2 diabetes At the time of
his diagnosis, Rep Bosleys blood sugar or glucose level was 250,
significantly above normal

Rep Bosley has had to make adjustments to his life to deal with his
diabetes He takes medication, checks his blood glucose, and monitors
his eating every day He has to be cautious about taking other
medications that may interact with either his diabetes medication or
affect his blood glucose adversely Having diabetes also means he has to
be careful about cuts that do not heal and make sure that his eyes, feet
and hemoglobin A1c levels, the average blood glucose level over the
previous 2-3 months, are checked yearly He also must worry about his
blood pressure and cholesterol

Rep Bosley has learned how diabetes affects his life on a daily basis
He states, Although my lifestyle as a legislator makes it difficult at
times, through changes in my daily routine, an exercise regimen, and a
better diet, I find that I can control my blood levels to the point where
I lead a pretty normal life

- An Interview
with Representative Daniel Bosley of
Massachusetts

For many years, leading health care analysts and researchers have
recognized that the quality of health care delivered by the American health
care system is varied While producing unrivaled innovation and new medical
treatments, in other ways the US health care system has difficulty
routinely and consistently translating research into practice, adhering to
guidelines for proper care, and improving health care outcomes This is
particularly true of diabetes care and care for other chronic diseases
McGlynn, Asch, Adams, et al, 2003

As the lead Federal agency charged with providing research on health care
quality, outcomes, and efficiency, the Agency for Healthcare Research and
Quality AHRQ recently released the first annual National Healthcare
Quality Report NHQR and the first annual National Healthcare Disparities
Report NHDR Commissioned by Congress, these reports provide extensive
data on the state of health care quality in the United States The NHQR
highlighted both important gains and continuing challenges to health care
quality in America In particular, the NHQR found strong evidence of wide
variation in the quality of
care for many diseases and conditions,
including diabetes The report makes clear that there is a sizable gap
between what experts recognize as the central elements of quality care and
the care that patients actually receive The NHDR also found that
differences in health care quality exist across racial, ethnic, geographic,
and socioeconomic groups

The NHQR and NHDR were not the first reports to document significant gaps
in quality in the US health care system In the groundbreaking report,
Crossing the Quality Chasm: A New Health Care System for the 21st Century,
the Institute of Medicine IOM issued a call to action to every actor in
health care to address this chasm The IOM specifically called on AHRQ to
identify and foster research on the 15 most expensive medical conditions in
order to focus quality improvement efforts
To stimulate efforts to improve the quality of care, AHRQ has published
this Resource Guide on diabetes quality improvement aimed at a variety of
State and local health care policymakers and leaders State leaders in
particular can play a key role in championing and fostering health care
quality improvement This Resource Guide also focuses on diabetes as
a
natural target for quality improvement The high cost of diabetes
complications-their long term effect on individual quality of life, the
high treatment costs, the fact that they are largely preventable, and the
possibility for a sizable return on investment-provide inherent incentives
for State leaders to assess the diabetes care in their State and identify
opportunities for quality improvement

Purpose of the Resource Guide

The purpose of this Resource Guide is to:

Provide an overview of the factors that affect the quality of care for
diabetes

Present the core elements of health care quality improvement

Provide data from the NHQR on diabetes to inform State decisionmaking

Offer a variety of best practices and policy approaches to diabetes
quality improvement

Assist policymakers and others in planning State-level quality
improvement initiatives

State leaders may lack State-specific data and research evidence that can
be easily synthesized and presented appropriately to inform decisionmaking
The NHQR, the NHDR and AHRQ are rich resources for providing both national
and State data on health care quality Using data collected from the NHQR
and the NHDR,
this Resource Guide will help State leaders understand the
issues surrounding diabetes quality improvement, evaluate the quality of
diabetes care, and construct quality improvement plans that are suited to
each States context AHRQ has developed this guide to provide States with
the resource information, framework, and guidance to help them understand
the issues involved in implementing a quality improvement program

Audiences for the Resource Guide

The delivery of high quality care happens in the clinical setting Thus,
quality improvement efforts ultimately need to affect what happens in a
doctors office, hospital, or other health care setting Even so, State
leaders and policymakers can have an enormous impact on health care They
can create a vision that inspires action and change They can involve
strategic partners and champions who can reach the front lines of health
care They can assemble information that grabs the attention of health
care providers at the local level, just as the NHQR does at the national
and State level As purchasers and regulators, States can supply
incentives for providers to make the changes necessary to improve the
quality of health care Through
State leadership, health care improvement
strategies can be fashioned more meaningfully for State and local health
care markets

Thus, the audiences for this Resource Guide include:

State elected leaders-Governors, legislators and their staff who provide
leadership on health policy

State executive branch officials-Executive office appointees and career
staff charged with taking action on important health issues, such as
State health department, Diabetes Prevention and Control Program DPCP,
and State Medicaid officials

Other nongovernmental State and local health care leaders- Members of
professional societies, provider associations, quality improvement
organizations, voluntary health organizations, health plans, business
coalitions, community organizations, consumer groups, and others who want
to stimulate action on health care quality improvement at the State
level

Structure and Organization of the Resource Guide

Figure I1 provides a macro-level view of the major components that State
policymakers need to effect quality improvement McNeill and Kelley, 2004
The model begins with gathering data and moves through generating
information from those
data for specific audiences, then into appropriate
action to effect change, and finally to the intended outcome-improvement
This conceptual framework shows the links or stages in the quality
improvement process that health system professionals must navigate to
accomplish real change The Resource Guide is divided into separate
modules that tackle each of these stages in the quality improvement
continuum Each module provides an explanation of the stages as well as
tools that State leaders can use to move to the next stage in the quality
improvement process

To assist State leaders with finding the information they need in this
guide, the beginning of each module has an outline of the contents and key
ideas Each module ends with a summary and synthesis to demonstrate how to
use the module to move to the next step Also, a resource list for further
reading and a discussion of associated appendixes are included where
applicable

Source: McNeill and Kelley, 2004

State leaders in different parts of State government have different roles
in quality improvement This Resource Guide attempts to reach a variety of
State leaders who have key and different contributions to make to
the
quality improvement process Once users know how the guide is organized,
they can skip to the sections that are most relevant and appropriate for
them For instance, the first module provides an overview of the issues
and is designed specifically for senior level elected and appointed
officials Subsequent modules, by contrast, provide more in-depth
information for specialists and technical staff such as Diabetes Prevention
and Control Program staff, legislative and policy analysts, quality
improvement specialists, and health data officials

The modules are organized as follows:

Module 1: Background helps to answer the following questions: What is
diabetes? What is quality improvement? Why should States care about
these issues? How can States be involved in diabetes quality
improvement?

Module 2: Data looks at the importance of data collection in assessing
quality and the role of quality measurement and examines a variety of
data sources on diabetes care quality that State leaders can use to
assess the quality of care in their States It specifically provides
process and outcome measures and estimates from the NHQR and NHDR
on
diabetes care Module 2 also provides guidance on selecting reliable
measures and collecting good data and discusses the inherent
limitations of particular data sources Finally, the module presents
data estimates on the direct and indirect costs of diabetes, including
the cost to Medicaid, for each State

Module 3: Information takes the next step in the quality improvement
chain by showing State leaders how to turn data into information to
answer key questions that should be understood before action is taken
This module examines the different benchmarks that States can use to
assess their States performance in providing quality diabetes care
An analysis using NHQR data from four States-Georgia, Massachusetts,
Michigan, and Washington-provides State leaders with concrete examples
of how one can draw conclusions from the data that can motivate local
action The module also analyzes various factors that affect health
care outcomes and the delivery of quality care, including
socioeconomic factors, biological and behavioral differences, and
health system characteristics, and the role
these factors play in
assessments of health care quality in the States

Module 4: Action provides State leaders with a variety of tools and
examples from diabetes care quality initiatives that can inform State
efforts The module will provide an overview of a variety of
national, public-private, Federal, State, and local diabetes quality
improvement initiatives Analyzing State action on diabetes quality
improvement, the module provides a catalog of State approaches with
brief examples from a variety of States, followed by profiles of
diabetes quality improvement approaches in California, Michigan,
Missouri, and North Carolina

Module 5: Improvement provides models, tools and checklists for State
leaders to use in crafting a quality improvement strategy for a given
State The module examines the Plan-Do-Study-Act model, which is used
frequently in quality improvement in clinical settings, and adapts
that model to State policymaking

Module 6: The Way Forward concludes the Resource Guide and examines
the opportunities for States to contribute to improving diabetes care

quality

In general, as State leaders begin the process of quality improvement, they
must make several key decisions This Resource Guide provides guidance
related to each of the following decision points:

1 Make quality improvement a priority Module 1: Background provides
evidence to use in making the case for diabetes care quality
improvement
2 Decide on a general topic areas for analysis This is discussed in
Module 2: Data
3 Identify measures that address the topic Module 2: Data describes the
NHQR measures that address diabetes care quality
4 Develop an inventory of data sources for the State or locality This
is pointed out in Module 2: Data
5 Determine benchmarks for the measures selected Module 3: Information
explains and identifies benchmarks from the NHQR
6 Conduct or commission analyses to create information that addresses
the questions raised Module 3: Information discusses creation of
information from data
7 Utilize an existing-or develop a new-advisory group, committee, or
workgroup focused on quality improvement This is reviewed in Module
4: Action An advisory group with internal and
external members can
help refine the topic, design the program, identify data and
information needs, recommend action, and champion the cause
8 Find resources to develop and support the initiative Ideas for how
to find financial support for diabetes quality improvement are
discussed in Module 4: Action Sources for information resources are
noted throughout the guide
9 Design and take action aimed to improve quality Module 4: Action
recounts a wide array of activities that have been undertaken by State
governments in the area of diabetes care quality
10 Evaluate the result Module 5: Improvement discusses evaluation
activities needed to assess the successes and challenges of quality
improvement efforts

Module 6: The Way Forward concludes this Resource Guide by summarizing the
key elements necessary in State efforts to promote diabetes care quality
improvement
Module 1: Background - Making the Case for Diabetes Care Quality
Improvement

About three years ago, New Hampshire State Representative Fran Wendelboe
discovered that she had pre-diabetes She tried controlling her diet,
losing weight and monitoring her
blood glucose on her own, but her hectic
schedule as an elected official and times of stress made this difficult
One morning she experienced trouble seeing and knew that she needed to
see her doctor

It was time for me to stop avoiding an official diagnosis and get
serious, actually past time, stated Representative Wendelboe I am now
on medication twice a day, but I am still struggling with my crazy
schedule and regular meal times This is not simple, even knowing that
the stakes are high

- An Interview with Representative Fran Wendelboe of
New Hampshire

The Importance of Diabetes

Diabetes is a serious chronic illness that affects a growing number of
people in the United States every year More than 18 million people have
diabetes One of the Nations leading killers, diabetes is a costly,
chronic disease that, if not diagnosed and treated properly, over the
course of time can lead to serious complications such as heart disease,
stroke, blindness, lower-limb amputation, kidney failure, disability, and
premature death

For many patients, it is years before they notice the warning signs of
diabetes and
are diagnosed Still others who are diagnosed lack adequate
treatment and do not know how to manage their disease well over time
Furthermore, the separate care environments that people with diabetes must
navigate due to the nature of their disease - eye, foot, heart, and various
internal medicine specialists, just to name a few - mean that it is
difficult for them to consistently receive the most effective care over
time

Why Should State Leaders Prioritize Diabetes?

As protectors of the publics health, State governments play a vital role
in preventing and controlling this disease Every State has public
resources invested in a Diabetes Prevention and Control Program that is
working to improve care for diabetes, although the level of investment
varies from State to State As health care purchasers, States are
responsible for ensuring that the health care they pay for on behalf of
State employees, Medicaid clients, and other recipients meets appropriate
standards of quality

State leaders are called to pay attention to many important issues during
the course of their work Making critical determinations of the relative
resources and attention that each issue should receive is
vitally important
for State leaders There are a number of reasons why States may want to
take a closer look at diabetes, including:

The rising prevalence of the disease graphically represented in Figure
11, including increases among children and adolescents, driven by an
aging and increasingly obese population

The long-term complications that can be prevented if diabetes is
diagnosed early and treated appropriately over time

The high health care cost of diabetes, primarily its complications and
the loss of economic productivity when disability or premature death
occurs

The disparities between various racial and ethnic groups in quality of
diabetes care

Interventions and treatment that can prevent type 2 diabetes and control
the development of complications for type 1 and type 2 diabetes

The potential for return on investment for purchasers and the health care
system as a whole through diabetes quality improvement

Rising Prevalence

According to the Centers for Disease Control and Prevention CDC, diabetes
currently affects over 18 million people, or 63 percent of the total
population CDC, 2003c Of those estimated to have the disease, more
than
5 million people do not know they have it CDC, 2003c Another 41 million
people are estimated to have prediabetes, a term used to describe the
condition of having an increased risk of developing type 2 diabetes CDC,
2003b

Trend data indicate that diabetes is rising at a rate faster than
population growth would alone indicate CDC, 2003a; Mokdad, Ford, Bowman,
et al, 2000 The development of diabetes has been strongly linked with
obesity, aging, and the increasing racial and ethnic diversification of the
population Ford, Williamson, Liu, 1997; Resnick, Valsania, Halter, et al,
2000 Diabetes affects older persons more frequently than younger
populations Of those over 65 years of age, 16 percent have diabetes,
whereas diabetes affects 2 percent of people between 20 and 44 years of age
Freid, Prager, MacKay, Zia, 2003 The prevalence of diabetes is also
higher among certain racial and ethnic groups, including blacks and
Hispanics AHRQ, 2003b Without intervention now to prevent and control
the onset of diabetes, rates could increase significantly as the large
number of baby boomers move into retirement and live longer

In addition to the aging of the population, the dramatic rise
of obesity in
the US population is also increasing the incidence of diabetes,
especially among children Mokdad, Ford, Bowman, et al, 2003 Since
1991, obesity rates have grown by 74 percent and diabetes rates have grown
by 61 percent CDC, 2003 Type 2 diabetes used to be called adult onset
diabetes because it almost never occurred in children and young people As
childhood obesity has increased, the incidence of type 2 diabetes in
children and young people has increased as well A CDC study estimates
that as many as one in every three children born in 2000 will develop
diabetes, if serious changes do not occur in diet, weight and exercise in
the American population Narayan, Boyle, Thompson, et al, 2003 The
earlier that diabetes develops the more likely that a patient will develop
complications and die prematurely

Figure 11

Long-Term Complications

Diabetes ranks as the Nations sixth leading cause of death, at a cost of
200,000 lives a year CDC, 2004 Experts believe that this death rate is
underreported because of the number of significant comorbidities associated
with diabetes, such as heart disease, stroke, and kidney disease that may
be coded as the cause of death
instead of the diabetes CDC, 2003c
The presence of too much glucose in the blood causes damage to blood
vessels and, subsequently, to nerves, organs, and tissues; over time this
results in various long-term complications, including:

Heart disease, hypertension, heart attacks, and stroke - People with
diabetes are at increased risk for high blood pressure and harmful levels
of cholesterol As a result, they also face increased risk of having a
heart attack or stroke Adults with diabetes have death rates from heart
disease that are 2 to 4 times greater than those without diabetes CDC,
2003c A person with diabetes has the same high risk for a heart attack
as a person who has had a previous heart attack Haffner, Lehto,
Ronnemaa, et al, 1998

Nerve damage - Nerve damage can lead to loss of feeling in the feet and
legs, stomach and digestion problems, sexual dysfunction, carpal tunnel
syndrome, and other nerve problems As many as 70 percent of people with
diabetes have some form of nerve damage CDC, 2003c

Ulcers and lower limb amputation - Nerve damage and circulation problems
in the feet and legs can contribute to sores and ulcers developing in

these areas Diabetic wounds often have trouble healing Uncontrolled
infections in the lower limbs can result in the need to amputate toes, a
foot, or a leg More than 60 percent of the amputations unrelated to
trauma occur in people with diabetes, making it the leading cause of
nontraumatic amputation CDC, 2003c

Eye problems and blindness - The small blood vessels in the eye can
become damaged, leading to blurred vision, increased risk for glaucoma
and cataracts, damage to the retina and blindness Diabetes is the
leading cause of new cases of blindness among adults between 20 and 74
years of age CDC, 2003c

Kidney disease and kidney failure - Damage to the fine blood vessels that
are responsible for filtering wastes from the body can harm the kidneys
If enough damage occurs, the kidneys fail This failure, called end
stage renal disease ESRD, means that individuals must undergo dialysis
or a kidney transplant to survive Diabetes is responsible for 44 percent
of new cases of ESRD, making it the leading cause of this disease CDC,
2003c

High and low blood glucose levels - Glucose levels in the blood that are
too high or too low
can cause people with diabetes to experience a number
of sudden problems, including shakiness, blurred vision, nausea, and
vomiting In serious cases, these imbalances can result in coma and
death

Other complications - Diabetes also increases the incidence of dental
disease and skin problems, increases the risk of infection, and poses an
increased risk for birth defects if pregnant CDC, 2003c; CDC, 2004

None of the complications listed above is an inevitable outcome of having
diabetes With quality care and proper self-management, individuals with
diabetes can prevent or delay the onset of these complications CDC, 2004

High Cost of Diabetes

In 2002, diabetes cost the United States 132 billion Of this, 92
billion was spent directly on medical care, while 40 billion was the
indirect cost associated with disability, diminished productivity and
premature mortality Almost 20 percent of health care spending goes to
treat people with diabetes Hogan, Dall, Nikolov, 2003

Diabetes is the sixth most expensive condition nationally Cohen and
Krauss, 2003 On average, medical expenditure for a person with diabetes
in 2002 cost more than 13,000 per year versus just 2,500
for the average
person without diabetes Hogan, Dall, Nikolov, 2003 About half of the
lifetime health care costs for patients with diabetes are related to
potentially preventable complications Herman and Eastman, 1998

Low-income populations for which States provide health care assistance are
very vulnerable to the complications of diabetes Medicaid pays 103
percent of the costs for treating diabetes, compared with 64 percent for
heart disease and 46 percent for cancer, the two most expensive medical
conditions Cohen and Krauss, 2003 To control Medicaid spending, States
have a financial stake in encouraging providers to give high quality care
to Medicaid recipients with diabetes Faulkner, 2003 Recognizing this
reality, more than 20 State Medicaid programs are using disease management
as a means to control costs while improving quality Brown and Matthews,
2003 Module 2: Data presents two data tables with estimates of the total
costs of diabetes for all 50 States and also costs just for Medicaid
populations in all 50 States These estimates are derived from the size of
the population and estimates of diabetes prevalence and costs per person
with diabetes based on judgments from
published research

In addition to Medicaid, private health plans and employers across the
Nation are increasingly looking to wellness programs, disease management,
and case management for diabetes as strategies to control health care
costs State governments, too, have struggled with rising health insurance
costs for State employees States, as employers, have financial incentives
to help employees, dependents, and retirees also avoid the consequences of
complications of diabetes Moreover, for people with diabetes who are
uninsured or who lack drug coverage, the costs of treating this disease can
be a crushing financial burden As a result, patients may forgo needed
medications or other care, thus increasing their chances for costly
complications later IOM, 2001c

Disparities in Health Care

Significant differences exist between racial, ethnic, and socioeconomic
groups in health outcomes for diabetes AHRQ, 2003b; IOM, 2003b For
instance, the NHDR found that blacks, American Indians, and Hispanics have
higher death rates for diabetes than whites Poor glycemic or blood
sugar control, serious complications from diabetes, and hospitalization
for complications were also more common in
blacks than other racial and
ethnic groups People with diabetes who had lower socioeconomic status
were also less likely to receive recommended care, such as eye exams, and
were more likely to be hospitalized for diabetes complications AHRQ,
2003b Such disparities may be due to barriers to health care access,
generally Overcoming these barriers, such as lack of insurance coverage
or ineligibility for public health programs, is a substantial challenge for
many individuals with diabetes

States and the Federal Government have actively sought to address health
care disparities as an issue of equity in the health care system
Disparities also raise questions regarding the effective use of resources
Care for low-income individuals who are hospitalized due to diabetes
complications is often financed by public sources such as Medicaid and
uncompensated care funds Ensuring effective care can help people with
diabetes to remain healthy and productive, prevent complications, and
reduce health care costs

Effectiveness of Interventions

Diabetes has tremendous impact on both public and private health care
spending and on the quality of life for those diagnosed with the disease
Yet type 2
diabetes, the most common form of diabetes, can be prevented and
controlled It is not inevitable that more Americans develop diabetes as
they age, nor is it inevitable that people with diabetes experience the
long-term complications such as lower limb amputations, kidney failure, and
premature death

Research indicates that diabetes prevention works Weight control and
regular exercise can prevent or delay the onset of type 2 diabetes The
Diabetes Prevention Program was a randomized clinical trial comparing diet,
exercise and treatment with metformin, a drug used to control blood glucose
levels, in 3,234 patients Knowler, Barrett, Connor, et al, 2002; Diabetes
Prevention Program Group, 2003 Conducted by the National Institute of
Diabetes and Digestive and Kidney Diseases, the trial demonstrated that
changes to diet and a moderate increase in physical activity reduced the
development of diabetes by 58 percent over 3 years; diet and exercise were
more effective than drug treatment in reducing diabetes Figure 12
Similar studies performed in China and Finland have also demonstrated
substantial reductions in the development of type 2 diabetes through
improved diet and exercise among
participants at risk for the disease Pan,
Li, Hu, 1997; Tuomilehto, Lindström, Eriksson, et al, 2001

Other studies have shown that proper health care and patient empowerment
can help control and minimize the complications of diabetes for those who
already have the disease The Diabetes Control and Complications Trial
DCCT Research Group studied individuals with type 1 diabetes and found
that intensive treatment for diabetes reduced eye disease by 76 percent,
nerve disease by 60 percent, and two forms of kidney problems by 39 and 54
percent DCCT, 1993 Another large, longitudinal study performed in the
United Kingdom found that aggressive treatment to lower blood glucose in
patients with type 2 diabetes resulted in the reduction of eye disease and
kidney disease by 25 percent The same study showed that reductions in
HbA1c levels was associated with a 35 percent reduction in damage to eyes,
kidneys, and nerves and a 25 percent reduction in the risk of premature
death from diabetes UK Prospective Diabetes Study Group, 1998

Patient self-management is particularly important for managing diabetes and
preventing complications Studies have demonstrated that patient self-
management
programs are effective tools for improving patient outcomes
One Stanford University study funded by AHRQ found that over a 2-year
period participants in a chronic disease self-management program showed
reductions in health distress, made fewer visits to the doctors office and
emergency room, had not experienced any further increases in disability and
had increased self-efficacy Lorig, Ritter, Stewart, et al, 2001
Systematic reviews of the literature on self-management programs for
diabetes found positive effects on patients knowledge, self-monitoring of
blood glucose, diet, and glycemic control Norris, Nichols, Caspersen, et
al, 2002; Norris, Engelgau, Narayan, 2001

Figure 12 Results of the Diabetes Prevention Program Study

State Diabetes Prevention and Control Programs, funded partially by CDC,
have been associated with noticeable improvements in diabetes prevention
and treatment; State DPCPs raise awareness of diabetes, primary and
secondary prevention, and quality improvement North Carolinas Project
DIRECT in its first year of operation helped increase diabetes patient
counseling for foot care from 20 to 50 percent Medical chart
reviews
showed improvement in monitoring of blood glucose, recommended screenings,
and diabetes education In New York State, work with community and
university partners helped to reduce hospitalization rates for diabetes by
35 percent and lower-extremity amputation by 39 percent CDC, 2003d From
1996 to 2001, Michigans diabetes program increased significantly the
number of recommended tests and screenings that people diagnosed with
diabetes received Hemoglobin A1c HbA1c tests increased from 14 to 78
percent, and foot exams increased from 58 to 77 percent In addition,
patients reported improved exercise and dietary planning CDC, 2003e

Ample research and experience from State DPCPs demonstrate that there are
successful tools for delaying and potentially preventing the development of
type 2 diabetes, managing both type 1 and type 2 diabetes effectively and
preventing the long-term complications that are responsible for high
treatment costs and diminished quality of life for people with diabetes

Potential for Return on Investment

Because diabetes can result in expensive long-term complications, public
health experts argue that investing in diabetes prevention and
control
initiatives today can improve health outcomes and reduce health care costs
Although the business case for diabetes prevention and quality improvement
is still being developed, a number of studies and the experience of both
public and private payers show promising signs regarding the return on
investment

A comprehensive economic analysis of the literature on 17 common diabetes
interventions sought to answer whether research has determined if diabetes
prevention and treatment is cost effective for society The study ranked
diabetes interventions based on whether the interventions were clearly cost
saving, clearly cost effective, possibly cost effective, not cost effective
or unclear The study determined a number of areas in which the benefits of
diabetes prevention and treatment provide a clear return on investment,
including eye screening and treatment, prenatal care, kidney disease
prevention, and improved control of blood glucose The study found no
diabetes treatments with costs that outweighed the benefits Klonoff and
Schwartz, 2000

Other convincing evidence that quality improvement for diabetes pays off
comes from studies of more intensive and comprehensive
treatment Two
studies analyzed the treatment costs of more intensive versus conventional
care for diabetes, one for type 1 and the other for type 2 Both studies
were based on the Diabetes Control and Complications Trial, a randomly
controlled clinical trial of intensive therapy for type 1 diabetes,
compared to traditional, less frequent treatment and contacts The trial
found that intensive therapy averted complications of the disease DCCT
Research Group, 1990 The two derivative studies simulated the lifetime
costs of diabetes-one for type 1 DCCT Research Group, 1996 and the other
for type 2 Herman and Eastman, 1998 The researchers reached similar
conclusions Even at two to three times the expense of conventional
therapy, the lifetime costs of improved care were offset by the lifetime
costs of blindness, end-stage renal disease, and lower extremity
amputations

A study of comprehensive care for diabetes in a managed care environment
demonstrated cost savings in as little as a 3-year period Sidorov, Shull,
Tomcavage, et al, 2002 The program, designed for six chronic diseases,
found per member per month paid claims averaged 39462 per enrollee with
diabetes in the comprehensive
care program compared to 50248 per enrollee
with diabetes not in the program That was a total saving for the health
plan of 43 million in paid claims annually for diabetes care, which
compared very favorably with an estimated 181 million cost including
capital expenses of the disease management program attributed to diabetes
care These cost reductions were accompanied by a higher proportion of
diabetes patients receiving recommended tests and monitoring

Another analysis of the business case for diabetes disease management
conducted by Harvard University for the Commonwealth Fund found that the
two health plans studied were able to cover the costs of their investment
in diabetes disease management programs, but did not save a significant
amount of money However, each patient enrolled in the program for 10
years would gain significantly in quality-adjusted life years Beaulieu,
Cutler, Ho, et al, 2003 The results of this study led the authors to
conclude:

The magnitude of the difference between costs and patient benefits
is so great that we believe, at the societal level, the outcomes of
these comprehensive [diabetes disease management] programs will always

be worth the investment needed Beaulieu, Cutler, Ho, et al, 2003

Americas Health Insurance Plans, a national trade association, evaluated
eight health plan programs in an analysis of cost savings from disease
management This analysis found that diabetes disease management programs
reduced hospital inpatient costs, number of days in the hospital, as well
as per member costs and total costs Disease management of multiple chronic
conditions, including diabetes, also showed evidence of significant
returns One plan with Medicare, Medicaid, and commercial enrollees found
that it saved 294 for every dollar invested in disease management for
multiple chronic conditions AAHP/HIAA, 2003

From 1999 to 2001, the Washington State Diabetes Collaboratives helped
reduce blood glucose for patients in participating health centers by 10
percent on average; and for patients with poor blood glucose control, it
was reduced from 24 percent to 17 percent, a 7-percentage-point reduction
The estimated annual cost savings from this improvement is roughly 419,000
a year CDC, 2003a Other studies have demonstrated that reducing HbA1c
levels from 10 to 9 percent in people with diabetes can result in
savings
of more than 1,200 per patient The savings can be as much as 4,000 in
patients with a combination of diabetes, heart disease, and hypertension,
which are common comorbidities of diabetes White, 2002

Other evidence from State disease management programs indicates that States
expect quality improvement for diabetes to help them reduce health care
costs Washington State hopes to save 900,000 through its Medicaid
diabetes disease management program Oregon expects to save 15 million
from its Medicaid disease management that targets diabetes, asthma, and
congestive heart failure Brown and Matthews, 2003

A growing body of research indicates that payers, patients, and society can
see a long-term return on investment in diabetes quality improvement Yet,
more research needs to be conducted on the types of interventions and
resource investments that may yield savings and under what circumstances
Most studies look at the cost effectiveness of one treatment or another but
do not consider the cost effectiveness of all interventions together such
as the DCCT study did The challenge of documenting cost savings from
diabetes interventions is that there are so many potential health
problems
to address for people with diabetes and so many combinations of
interventions to assess Tracking and data management are difficult to do
Cost savings are difficult to calculate accurately because of measuring
savings for people who are unaware that they have diabetes and for those
diagnosed who are not using health care services and are not managing their
disease Most importantly, the available evidence points to the fact that
the largest savings from diabetes interventions can occur many years into
the future-a difficult investment horizon for businesses and legislative
budget analysts who may be looking for short-term savings While more
research needs to be done, there is reasonable evidence that diabetes
interventions can yield cost savings and little doubt that available
interventions can improve the quality of diabetes care and health outcomes
over the long term

The NHQR and NHDR as Resources for State Leaders

The NHQR and NHDR serve as a snapshot of national health care quality by
providing a means to assess where the health care system is doing well and
where there are areas for improvement These first reports offer baseline
estimates using current data, and
subsequent reports will compare future
years of data against these baselines to assess whether the United States
is improving the quality of health care

For State leaders, it is important to understand several key findings from
the NHQR First, on many measures, there is a large gap between what is
recommended care for patients and what the patient often receives
Further, there is considerable variation in the care that individuals with
the same condition receive from State to State and, for some measures,
region to region The NHDR also found that there is considerable variation
in care among population groups and socioeconomic characteristics, such as
age, race, ethnicity, education, and income level

Gaps Between Recommended Care and the Care Received

Clinical guidelines for diabetes care recommend that people with diabetes
receive several important tests and a vaccination for influenza annually in
order to prevent future complications American Diabetes Association [ADA],
2004a There is large variation in how often people with diabetes receive
recommended tests and influenza vaccination The NHQR reports that:

According to AHRQs Medical Expenditure Panel Survey MEPS, a
national
data source, the vast majority of patients with diabetes-89 percent
nationally-receive an HbA1c test within the year

According to State data from the CDCs Behavioral Risk Factor
Surveillance System BRFSS, nearly half of all people with diabetes do
not receive a vaccination for influenza annually as recommended by
diabetes care guidelines Furthermore, the vaccination rates across the
States vary tremendously-from 17 percent to 64 percent

According to the same source, nearly one-third of diabetes patients do
not have a retinal or foot exam annually Across States, the rates range
from 50 percent to 83 percent for retinal exams and 50 percent to 87
percent for foot exams

According to the CDCs National Health and Nutrition Examination Survey
NHANES, only 37 percent of adults diagnosed with diabetes have HbA1c
levels in the optimal range There are no State estimates for this
measure See Module 2: Data and Appendix C for further explanation of
these data sources

These facts highlight where the Nation is doing well and where there is
room for better processes regarding diabetes care The States with the
highest rates on the
diabetes measures above-the best-in-class States-also
provide examples of quality performance that is achievable

Variation in Care Across States

As the list above indicates, there is considerable variation in diabetes
care from State to State Yet, diabetes has well-developed national
guidelines for the care that people with diabetes should receive This
variation suggests considerable room for improvement for some States in the
quality of diabetes care

Table 11 summarizes State-generated estimates for four diabetes care
quality measures from the Behavioral Risk Factor Surveillance System
BRFSS, collected by States and coordinated by the CDC
The BRFSS reports that States have a two-fold range of 48 to 89 percent of
their residents with diabetes receiving an annual HbA1c test A similar
spread between the States occurs for foot exams; a slightly smaller
difference occurs for eye exams Influenza immunizations, however, have a
four-fold difference between the high and low State rates

Table 11 also gives the Healthy People 2010 HP2010 baselines and goals
for objectives similar to the measures used in the NHQR Comparing the
first column, State averages, with the HP2010 measures, it
is evident that
States have made considerable progress from the 1998 baseline estimates for
most of these measures There is room for improvement on some goals and
considerable room for improvement compared to the performance of the best
or top-decile States
Variation in Care Across Population Groups

The NHQR and NHDR also document variation in care across a number of
different population characteristics The NHQR provides information on
variations in quality measures by:
Age
Sex
Educational level
Employment status
Health insurance status public/private/uninsured
Income level
Metropolitan/non-metropolitan location
Health status

Table 11 Quality measures for diabetes care: All-State average, top-
decile States average, and State range for 2001, the HP2010 baseline for
1998, and HP2010 goal for 2010

The NHDR documents the variation in the quality of and access to health
care across subgroups of race, ethnicity, income, education, and place of
residence

The data from the NHQR and NHDR, as well as findings from other research,
show that a variety of care for diabetes AHRQ, 2003a and 2003b African
Americans, American Indians, Asian Americans, Hispanics/Latinos, and
Pacific Islanders are more likely than non-Hispanic whites to have diabetes
CDC, 2004; AHRQ, 2003b In addition, across some measures for diabetes,
racial and ethnic minorities receive less recommended care than whites do
and have higher rates of hospitalization for long-term complications of
diabetes AHRQ, 2003b However, one study demonstrated that racial and
ethnic disparities are moderated when people are involved in a regular
system of care Karter, Ferrara, Liu, et al, 2002

Also, people with incomes below the poverty level and those with less
education are more likely to develop diabetes and its complications
Individuals with lower incomes and those with less than a college education
also were lower than the national average across most
diabetes quality
measures AHRQ, 2003a and 2003b All of these findings are important to
recognize as States undertake diabetes quality improvement initiatives,
because the racial, ethnic, and socioeconomic makeup of a given State
influences the underlying factors that affect diabetes care quality

The variation in quality across the Nation, across States, and among
various population groups highlight opportunities for improvement States
with below average rates on a given quality measure have clear guidance on
which areas to address related to diabetes care quality Also, low
performers may be able to make small changes with big results
Additionally, States that score highest on a given quality of care measure
can provide a benchmark for other States to aim for and indicate what is
possible

The Quality Improvement Opportunity

In recent years, interest in addressing health care quality has increased
tremendously The publication of the Institute of Medicines IOM
reports, To Err is Human and Crossing the Quality Chasm, has helped spur
interest in medical errors, patient safety and quality improvement The
releases of the NHQR and NHDR have also provided added attention to
health
care quality as an issue for Federal and State policymakers

In its report, Fostering Rapid Advances in Health Care, the IOM outlined a
variety of strategies to advance public policy around quality improvement,
including attention to care for chronic diseases The report emphasized
the role of States along with the Federal government in quality
improvement Secretary of Health and Human Services Tommy G Thompson has
stated that State and local demonstrations are needed to test a variety of
quality improvement approaches, evaluate the effectiveness of the different
models, and inform national efforts IOM, 2003a States already have
undertaken disease management pilots and other demonstration projects
related to quality improvement using funds from the CDC, Medicaid, and
Medicare see Module 4: Action for more information on the kinds of
programs

States are critical partners in quality improvement with strategic
implications for the future of health care There is commitment at the
national level to quality improvement What is needed now is action

Both the NHQR and IOMs Crossing the Quality Chasm report highlight the
importance of improving care for chronic diseases
Diabetes in particular
is recognized as one chronic disease for which quality improvement efforts
could make great strides Diabetes has widely respected national
guidelines for what constitutes quality care and well-developed national
measures of quality Despite this fact, the gap between evidence-based
treatment and actual practice and outcomes continues to be wide There
continues to be a large number of complications from diabetes that research
demonstrates could have been prevented with high quality care States can
play a key role in fostering diabetes quality improvement

Summary and Synthesis

This module has provided background on diabetes as a disease and its
associated costs, complications and prevalence This module has also
examined the evidence from both NHQR and NHDR regarding the substantial
gaps in care quality for diabetes that exist across the Nation, between
States, and across population groups

Because of their roles as health care purchasers for Medicaid and State
employees as well as their role in protecting the publics health, States
have a vested interest in championing prevention of and quality improvement
for diabetes Particularly in an age of rising
health care costs, States
cannot afford simply to pay for business as usual in health care Evidence
from research indicates that quality improvement is critical to achieving
better health outcomes and closing the gaps between what we know and what
we do in health care In addition, there is growing evidence that
investments in diabetes quality improvement can yield a significant return
on investment both in terms of cost savings and improved quality of life
for people with diabetes Fortunately, there are both existing policy
models and new resources that State leaders can use to assess diabetes care
quality in their States and devise quality improvement plans

With a background and understanding of the issues related to diabetes
quality improvement, the next step in the quality improvement process is to
formulate a set of questions and gather the data to answer them The NHQR
and the NHDR are rich data resources for States to use to help answer
questions about the quality of diabetes care in and across States Module
2: Data presents NHQR and NHDR data Module 3: Information analyzes the
data and provides examples of how States can use the data to make
comparisons and assessments
of where to focus State efforts to improve
diabetes care quality Module 4: Action presents various diabetes quality
improvement approaches that States can use as models for action The final
modules are designed to help State leaders to devise quality improvement
strategies that are suited to local settings and circumstances but that
draw on national, Federal, and State data and models for action

Resources for Further Reading

National Healthcare Quality Report and National Healthcare
Disparities Report, available at: http://wwwqualitytoolsahrqgov

Institute of Medicines Crossing the Quality Chasm: A New Health Care
System for the 21st Century, available at:
http://wwwiomedu/reportasp?id5432

Institute of Medicines Fostering Rapid Advances in Health Care:
Learning from System Demonstrations, available at:
http://wwwiomedu/reportasp?id4294

Associated Appendix for Use With This Module

Appendix A: Acronyms Used in This Resource Guide

The acronyms employed to describe the organizations endorsing the NHQR
quality measures are described in Appendix A, along with all other acronyms
used throughout this Resource Guide

Module 2: Data
- Understanding the Foundation of Quality Improvement

Health care is crucial to our quality of life and is one of the biggest,
and probably the fastest growing financial burdens for government,
business and individuals It is complicated, and we are learning by
experience Good decisions will make the State healthier and the State
economically competitive, poor decisions will not We need reliable and
current data to make good decisions

- Robert Huefner, PhD, Member, Utah Health Data Committee
Testimony to the Health and Human Services Appropriations
Committee, January 10, 2002

A key ingredient to improving health care quality is data The term data
usually refers to values or estimates generated to describe a concept and
to track it over time, space, and populations Data reveal the extent of a
problem, the subpopulations involved, and the geographic disparities in
outcomes and processes of care Data are necessary to make the case for
diverting scarce State resources staff or budgets to a quality
improvement initiative

Exploring available data is a productive way to begin the process of
identifying quality problems and selecting
and defining an improvement
project Furthermore, the quality improvement process is a cycle
explained in Module 5: Improvement that rests on the backbone of data
Data are necessary to assess the situation at a baseline and ultimately to
determine whether an intervention is accomplishing what was intended or
whether objectives and actions need to be changed to improve quality

The National Healthcare Quality Report, with national and sometimes State-
level data, is a valuable resource for reviewing and comparing health care
quality across the States It is a source of accepted measures and
benchmarks for comparison Benchmarks are explained in Module 3:
Information

This module discusses the basic building blocks of quality improvement -
measurement and data The Module describes the diabetes-related data
available in the NHQR and other relevant data sources that States can use

Even when data are not readily available, estimates can be generated by
assembling information from various sources Two practical examples of
this are developed in this module for the Medicaid and State populations
The results of research studies combined with national and State databases
are used to
estimate the Medicaid spending on diabetes care and the cost
burden of diabetes to each State

What this module does not address are the wide-ranging possibilities,
constrained only by resources, of collecting data through surveys tailored
to planned projects and aimed at measuring the scope of the quality problem
and evaluating the effectiveness of planned interventions Each State has
a cadre of health statisticians and analysts who should be recruited to be
part of any quality improvement project aimed at the health care system in
the State

Quality Measurement

Background

This section reviews the concept of quality measurement, available diabetes-
related measures in the NHQR, and the importance of using multi-dimensional
measure sets All of this is from the perspective of State quality
improvement programs

Conceptual design of quality measures is necessary before data collection
can begin What is to be measured? How should it be measured? How will
it be analyzed?

Fortunately, finding measures of health care quality is not difficult
Much work has been done over the past 30 years to advance the field of
quality measurement In fact, the plethora of measures can
actually
frustrate health care providers and analysts: Which should be used to
guide and evaluate a quality improvement program? What do the measures
mean? How should individual values be interpreted?

Quality measures cover a large range, from crude measures eg, unadjusted
mortality rates to more refined measures eg, percent of an at-risk
population achieving glycemic control as evidenced by HbA1c levels While
a full range of measures is essential for a complete picture of health care
quality, specific process measures are needed to move a health care team
toward delivering quality care For example, the number of deaths at a
hospital can suggest poor quality of treatment at that hospital, but
knowing the number of deaths does not tell the hospital staff how to
improve Quality measures of processes of care that are linked to
increases or decreases in deaths or other medical outcomes help medical
staff know how to change care in order to improve patient outcomes

There is a distinction between quality measures and guidelines for quality
care The health care quality measures used in the NHQR and used for State,
regional, or local planning for quality improvement initiatives
relate to
populations Such measures are often rates eg, percentages which
indicate the number achieving a goal eg, glycemic control relative to a
population base eg, all people with diabetes in the Nation

By contrast, guidelines for quality care are recommendations devised via
consensus processes of clinical experts that describe standards of care for
individual patients In general, guidelines for quality care of individual
patients are used as the theoretical underpinning to develop population-
based quality measures

Most quality improvement efforts focus on process and outcome measures see
text box below Process measures often reflect evidenced-based guidelines
of care for specific conditions Outcome measures often relate to patient
health status Ideally, improvement in a particular process measure yields
improvement in the associated outcome measure Structural measures of the
health care infrastructure are a third type of quality measure, less
directly related to quality of care

Diabetes-Related Quality Measures in the NHQR

Although many process measures exist for diabetes care, those listed below
survived an extensive consensus process developed for the NHQR and
could be
estimated from national databases See Appendix C for more information on
national quality measurement activities and the NHQR measure selection
process The NHQR uses five process measures and seven outcome measures;
the outcome measures are of two types-test results and avoidable
hospitalizations

Process Measures

HbA1c test-Percent of adults with diabetes who had a hemoglobin A1c
measurement at least once in the past year

Lipid profile-Percent of patients with diabetes who had a lipid profile
in the past 2 years

Eye exam-Percent of adults with diabetes who had a retinal eye
examination in the past year

Foot exam-Percent of adults with diabetes who had a foot examination in
the past year

Flu vaccination-Percent of adults with diabetes who had an influenza
immunization in the past year

Outcome Measures

Test results-The NHQR uses the three measures listed below:

o HbA1c levels-Percent of adults with diagnosed diabetes with HbA1c
levels 95 percent poor control; 90 percent needs
improvement; and 70 percent optimal control

o Cholesterol levels- Percent of adults with diagnosed diabetes with
most
recent LDL-C level 130 mg/dL needs improvement; 100
optimal

o Blood pressure-Percent of adults with diagnosed diabetes with most
recent blood pressure 140/90 mm/Hg

Avoidable hospitalizations-The NHQR uses the four measures listed below:

o Hospital admissions for adults with uncomplicated, uncontrolled
diabetes per 100,000 population

o Hospital admissions for adults with short-term complications of
diabetes per 100,000 population

o Hospital admissions for adults with long-term complications of
diabetes per 100,000 population

o Hospital admissions for lower extremity amputations for patients of
all ages with diabetes per 1,000 population

Ideally, improvement in a process measure will yield improvement in an
associated outcome measure An example of this, used by the NHQR is the
diabetes process measure of an annual HbA1c test to monitor blood glucose
levels Control of blood glucose in people with diabetes has been
connected with the delay of complications Such complications often result
in hospitalization Hospitalizations for uncontrolled long-term and short-
term complications of diabetes
are outcome measures used in the NHQR In
this case, improvement in the process of monitoring HbAlc is expected to
decrease the number of such hospitalizations, as diagramed in Figure 21
Of course, the connections are never that simple or direct An HbA1c test
does not necessarily mean that a patient will self-manage the disease
sufficiently or the clinician will provide the appropriate intervention to
lower an HbA1c level and decrease long-term complications Effective
patient and provider education is a crucial link

Figure 21 Relationship of a diabetes process and outcome measure

Sources of NHRQ Data on Diabetes Care

This section describes actual estimates for the diabetes measures above
from the NHQR as well as other sources of data that may help States
generate estimates or analyze factors related to the quality of diabetes
care The quality of the data itself is discussed throughout this section,
because State leaders in quality improvement must understand issues that
will be raised in the improvement process Health care providers may argue
that the data, due to limitations, do not reflect reality They may say:
The data are the problem and not the health
care system Understanding
data limitations leads to responsible use of data

The NHQR uses many different data sources see Appendix B for a complete
list Different sources use different methods, definitions, and
classifications Some sources produce estimates by State and some by
national population subgroup, such as race/ethnicity, gender, age, and
income

The diabetes data in the NHQR come from five data sources:

Behavioral Risk Factor Surveillance System, a telephone survey designed
by the CDC and conducted by individual States BRFSS data are the only
diabetes-related data reported by State in the NHQR except for a special
analysis using HCUP data discussed in Module 3: Information BRFSS
provides State-level estimates for four of the five process measures

Medical Expenditure Panel Survey-Household Survey, a national in-person
survey, conducted by AHRQ MEPS data are used for all five process
measures and report data by national population subgroup

National Health and Nutrition Examination Survey, a physical examination
survey conducted by clinicians who staff a tractor-trailer clinic that
travels to sampled communities under the auspices of the
National Center
for Health Statistics NCHS/CDC NHANES is used for two laboratory value-
related outcome measures that require clinical data from physical
examinations

Healthcare Cost and Utilization Project HCUP, a census of hospital
discharge records for States 29 in 2000 in a Federal-State-Industry
partnership, sponsored by AHRQ HCUP data are used to report on three
outcome measures of avoidable hospitalizations

National Hospital Discharge Survey NHDS, a national sample of hospitals
and a sample of their discharges, conducted by NCHS NHDS is used for one
outcome-related avoidable hospitalization

General information on each data source and its limitations are presented
next The most detail is presented on BRFSS because it is the only NHQR
diabetes data that reports by State Following those discussions, Table 21
presents the State-by-State rates for the four BRFSS process measures
Appendix C includes a more in-depth discussion of each data source and
other NHQR data tables Data tables in Appendix C from sources other than
BRFSS present national rates and data by subgroup

Process Measures-BRFSS and MEPS Data

Behavioral Risk Factor Surveillance
System

BRFSS data used in the NHQR are from 2001; in that year, 41 States
collected data for three of the five diabetes process measures in the NHQR
Those measures include annual HbA1c testing, foot exams, and eye exams
All 50 States collected data on receipt of influenza vaccination in the
past year

The BRFSS data are based on telephone surveys developed by the CDC but
administered by each State independently The survey consists of a core
set of questions developed by CDC, additional questions developed by the
States, and separate, optional modules for States to use The diabetes
module, which contains the quality-of-care questions, is optional for State
use More information about the BRFSS data and methods as well as
interactive databases with some State and local level diabetes data are
available at: http://wwwcdcgov/brfss/

Limitations of BRFSS data: Every data source has limitations They relate
to the population represented, methods used to collect the data,
definitions, and analytic approaches These factors affect the estimates
generated from a data set When similar measures from two data sets
differ, the cause can usually be traced to the limitations of the
data
sets By understanding the limitation of a data set, the strengths and
weakness of estimates from the data set can be assessed and the estimates
can be used more responsibly Limitations of BRFSS data include the
following:

BRFSS samples are kept small to minimize survey costs for States The
State BRFSS samples for the year 2001 range from 1,888 to 8,628
respondents see:
http://wwwcdcgov/brfss/technical_infodata/surveydata/2001/codebook_01
rtf For respondents with diabetes the sample is even smaller,
generally around 200 Mukhtar, Murphy, Mitchell, 2003; Safran,
Mukhtar, Murphy 2003 Small samples increase the variance of
estimates and decrease the size of the difference between two
subpopulations that can be detected through the survey responses

The BRFSS survey excludes people without a residential phone and
people who are institutionalized This means that the total
population of interest-all people with diabetes-will not be
represented in the estimates that come from the survey Nelson,
Holtzman, Bolen, et al 2001 This weakness can be dealt with by
carefully discussing BRFSS results
in relation to the population it
represents

BRFSS data are self-reported and reflect the perceptions of
respondents An advantage of self-reports is that they can reveal
information that cannot be obtained from other sources; for example,
the receipt of flu vaccinations for people who dont see a doctor
during the year A disadvantage of self-report data is that
respondents may have difficulty recalling events, understanding or
interpreting questions, or responding truthfully to questions about
socially unacceptable behaviors Furthermore, cultural and language
barriers and limited health knowledge can affect the quality of self-
reported data Nelson, Holtzman, Bolen, et al 2001 These problems
may occur with different propensity for different subgroups

BRFSS data, like most surveys, are limited by budget constraints
Because BRFSS is funded by State which vary considerably in the levels
of their budgets allocated to health surveys, these fiscal disparities
may affect the quality of the data across States Such data quality
shortcomings can include bias from differential response
rates,
varying followup periods, and variations in interviewer protocols
eg, extent of probing for answers

Addressing small sample size limitations: One way to deal with small
samples is by pooling data over two or three years In 1999, when the CDC
incorporated evaluation and program accountability requirements for the
State diabetes control programs, it provided baseline estimates of State
rates for HbA1c testing, eye exams, foot exams, and self-monitored blood
glucose by pooling the data from 1997 through 1999 A more stable baseline
facilitated comparisons among the States and enabled States to monitor
improvements Safran, Mukhtar, Murphy, 2003 Tables C6 throughC10 in
Appendix C include these baseline estimates and BRFSS trends for various
years

Because the NHQR uses data from only one year, Module 3: Information takes
sample size into account when interpreting the data on diabetes quality
measures from BRFSS

Despite limitations, BRFSS diabetes data are widely used by State DPCP
coordinators Seventy percent of State coordinators surveyed reported that
they used those data for program evaluation, publications, or program
implementations When rating the
usefulness of the questions in the
diabetes module, State coordinators rated HbAlc testing, eye exams, foot
exams, self-monitoring of blood glucose, and diabetes education as highly
useful Mukhtar, Murphy, Mitchell, 2003

BRFSS estimates for diabetes care quality: Table 21 shows estimates for
the four NHQR measures derived from BRFSS and includes estimates for the
revised HP2010 objective for HbA1c testing at least twice annually These
estimates are reported nationally over all 41 contributing States and by
individual State Each of the four measures includes the estimate of the
rate per 100 people or percent and the standard error of the rate which
is affected by the sample size

Table 21 also indicates statistical significance for each State compared
to the national average and the top decile of States The top decile or
best in class benchmark is explained in Module 3: Information Two
different statistical significance tests are represented in symbols as
follows:

Test of difference from the national average-For this test, the symbols
and - represent the State rate that is statistically above or
below - the national average States with no adjacent symbol are not

statistically different from the national average

Test of difference from the average of the best-in-class States-For
tests of difference from the top-decile States, the symbol indicates
States that are indistinguishable from the best-in-class States
States without the symbol are statistically different from the best-in-
class average

The maps in Figure 22 summarize the five BRFSS measures found in Table 21
in relation to the national average rates The hues show which States are
statistically significantly below or above the average, those that are not
different from the average statistically, and those that do not collect
data

Table 21 Percent of non-institutionalized adults 18 and over with
diabetes who reported having important diabetes tests or health services
in the past year, age adjusted, by State, 2001

Figure 22 States above, below, and at the national average for important
clinical processes for the noninstitutionalized population with diabetes

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Medical Expenditure Panel Survey

The NHQR uses data from the Medical Expenditure Panel Survey to report
national rates by national subgroup for five process measures Four
measures are the same as those from BRFSS-HbA1c testing, eye exams, foot
exams, and influenza immunizations The fifth measure is lipid profile-the
percentage of people with diabetes who reported receiving a test for lipid
profiles in the past 2 years

MEPS is a family of surveys, including a household survey and surveys of
related health care providers Information is collected annually on
health care utilization, expenditures, and health insurance coverage For
the most part, MEPS data are collected using computer-assisted, in-person
interviews The diabetes component is collected via a separate paper and
pencil questionnaire distributed to respondents who report that they have
been diagnosed with diabetes More information about MEPS data and methods
are available at http://wwwmepsahrqgov/WhatIsMEPS/OverviewHTM

Differences between MEPS and BRFSS: MEPS reports on the same process
measures as BRFSS nationally but does not produce State-level estimates
Notable differences exist
between MEPS and BRFSS national rates for HbA1c
testing and influenza immunization The HbA1c MEPS-BRFSS difference 90
percent versus 79 percent is due to different survey response options and
the order of the questions The MEPS-BRFSS influenza immunization
difference 55 percent versus 37 percent is due to different age-group
definitions between the two surveys; the MEPS rate is for adults age 18 and
over; the BRFSS rate is for adults age 18 to 64 Since flu shots are less
likely to be given to younger than to elderly people, the BRFSS rate is
lower than the MEPS rate More information on differences between MEPS and
BRFSS is provided in Appendix C

Outcome Measures-NHANES, HCUP, and NHDS Data

National Health and Nutrition Examination Survey

The NHQR uses data from the National Health and Nutrition Examination
Survey for two outcome measures related to diabetes-the average blood
glucose level over the prior 2 to 3 months and blood pressure at
examination NHANES, which uses a relatively small sample size because of
the costliness of conducting physical examinations in communities, does not
support State-level estimates NHANES does provide estimates for the
Nation that could be
used as benchmarks over time These benchmarks would
be valuable to a State that has the same clinical measures for some
population within the State such as health systems with electronic medical
records or if the State establishes special data collection through health
care providers for such measures Note: To be comparable to data from
providers, the NHANES HbA1c and blood pressure values would have to be
recalculated to exclude people who do not use the health care system during
a year Additional information on NHANES is available at:
http://wwwcdcgov/nchs/about/major/nhanes/NHANES99_00htm

Healthcare Cost and Utilization Project
The NHQR uses inpatient discharge data from the Healthcare Cost and
Utilization Project for national estimates of three outcome measures of
avoidable hospitalizations related to diabetes HCUP is a public-private
partnership sponsored by AHRQ with 29 participating States that covers
about 80 percent of US discharges in the United States in 2000, the time
for which data are included in the first NHQR While national diabetes
estimates from HCUP are included in the NHQR, State-level data are not,
except for one special analysis of admissions for
uncomplicated
uncontrolled diabetes discussed in Module 3: Information Additional
information on HCUP data is available at: http://wwwhcup-
usahrqgov/overviewjsp
AHRQ also has developed the Quality Indicators AHRQ QIs for use with HCUP
and other hospital administrative data AHRQ, 2001, 2002, 2003 The AHRQ
QIs use sophisticated clinical algorithms of inclusions and exclusions to
define patient groups at low risk of poor health outcomes and then
calculate the outcomes of these low risk groups across different settings
and populations The algorithms have been tested, reviewed, and hewn by
clinical consensus panels under AHRQ sponsorship The AHRQ QIs include the
Prevention Quality Indicators, which estimate rates of avoidable
admissions, including diabetes admissions, as an indirect measure of the
quality of ambulatory diabetes care in the United States As tools for
local quality improvement, the AHRQ QIs can be used as screens for quality
problems that call for more in-depth local study; they are not considered
definitive measures of local quality of care As national measures they
capture trends in quality as well as coding of diagnoses National
estimates of the Prevention
Quality Indicators are part of the first NHQR
and NHDR Additional information on the AHRQ QIs is available at:
http://wwwqualityindicatorsahrqgov/
Limitations of HCUP data: The main limitation of HCUP data or any
administrative billing data is that the data are collected for the purpose
of payment, and what is coded as clinical diagnoses and procedures can be
affected by reimbursement incentives Keating, Landrum, Landon, 2003
Such incentives can encourage or discourage coding of specific types of
conditions or treatments Nevertheless, HCUP data can be used for many
purposes, provided that the bias of coding is considered and ruled out as
inconsequential Thus, while administrative hospital data can be mined for
clues to quality of care, analysts should be alert for whether the data
contain incomplete entries or inadequate clinical detail

National Hospital Discharge Survey

The NHQR used the National Hospital Discharge Survey for one outcome
measure-lower extremity amputations The NCHS at CDC uses a national
sample of hospitals and a sample of their discharges to collect
administrative hospital records for the NHDS similar to HCUP The sample
consists of about 270,000 inpatient
records from about 500 hospitals and is
representative of inpatient discharges nationally Additional information
on NHDS data is available at:
http://wwwcdcgov/nchs/about/major/hdasd/nhdsdeshtm

Limitations of NHDS data: The limitation of NHDS data are similar to those
for HCUP data described above because NHDS also uses discharge records or
inpatient claims for reimbursement In addition, although NHDS is a true
probability sample, it has a much smaller sample size than HCUP As a
result, many subgroup estimates that can be made with HCUP cannot be
supported with NHDS data

Filling Local Data Gaps

Finding data is a challenge for quality improvement programs Two avenues
can be used to locate relevant data: 1 developing an inventory of local
data sources and 2 using published research to generate local estimates
The latter generating local estimates is acceptable for planning
purposes, until better local sources are located and analyzed One of the
best sources for filling the data gaps will be the State DPCP staff

Developing an Inventory of Local Data Sources

Local data whether State, county, municipal, or individual health care
provider data are essential for quality
improvement programs to have an
impact locally Local leaders and health care professionals must see their
own data in comparison to other providers and to State, regional, and
national benchmarks in order to appreciate the importance of their work

Health care quality improvement programs should develop a complete
inventory of data systems available at the State and local level Doing so
may reduce data-related costs and avoid duplicate data collection Also, a
review of local data in the context of the NHQR and NHDR should make clear
where existing local surveys or data systems could be modified to add
information comparable to the concepts used in those reports and, thus, to
provide the raw materials for insights into health care and its quality at
the local level

Most States have data systems that can contribute to a review of health
care quality at the State or local levels Some of those data systems
include:

BRFSS data, available at the State level through the State health
department

Statewide inpatient hospital discharge systems, for which HCUP and NHDS
data can provide uniform national comparisons

State vital statistics, which include mortality rates by
cause of death
and for which the National Vital Statistics System can provide uniform
national comparisons

Special disease registries, some of which are focused on diabetes

Other special data collection of State departments of health statistics
and other State programs

Specific data systems for populations that the State supports are also
available in most States These include:

Medicaid information systems based on health care provider claims for
reimbursement from Medicaid

State employee health benefit claims for reimbursement

Patient records from State- or county-run programs, such as mental health
and substance abuse programs or school health programs

Some examples of State-level data sources are available at the National
Association of Health Data Organizations Web site
http://wwwnahdoorg/soa/soalist1asp?CategoryState20Agency

Other Federal or national systems compile data that describe State and
local populations or health resources These include:

The CDCs Division of Diabetes Translation Web site, a valuable starting
place to identify data and become familiar with the network of
organizations and individuals associated with diabetes
data collection at
the State and national level
http://wwwcdcgov/diabetes/statistics/indexhtm

Census population data by State, maintained by the US Bureau of the
Census http://eirecensusgov/popest/data/statesphp

The Area Resource File, a county- and State-level database of health care
resources from several surveys and data sources, compiled by the Health
Resources and Services Administration HRSA

Quality of care in managed care organizations, provided through the
National Committee for Quality Assurance see: http://wwwncqaorg/
Local managed care organizations can be an important source of local
data on health care quality

The Henry J Kaiser Family Foundations Web site
http://kfforg/statepolicy/indexcfm, a rich source of health and other
information at the State-level compiled from many public databases and
published studies

Using Published Studies and Readily Available Data To Develop State or
Local Estimates

Before resources are invested in data collection targeted to an improvement
goal, some information can be assembled from existing sources and published
research studies Sometimes published studies on a topic can be used
to
derive estimates at the State or local level These ballpark estimates
should be replaced by more accurate local data when they are available

To assess the impact of diabetes on the State, studies of diabetes
nationally might be used For example, if a national study shows how
subgroups differ in diabetes prevalence or costs and provides estimates by
those general subpopulations eg, age groups, then those general
subpopulation characteristics in the State or locale can be applied to
the national rates, thus resulting in State or local estimates for
diabetes

The more detailed and compatible the data are across sources, the better
the estimate will be However, existing data details are seldom
sufficient, which limits the confidence of estimates that can be made from
existing tables and published estimates When this is the case, original
analyses of the underlying data may be necessary When actual data are
available from State agencies for all or part of the information
components, they are preferable to estimations from national data

Two examples of deriving State estimates from national data and studies are
presented here: 1 Medicaid spending on diabetes care, and 2 total
cost
burden of diabetes, by State

Example One-Medicaid Spending on Diabetes Care: This example derives
estimates of spending on diabetes care for State Medicaid agencies using
the following components:
National diabetes prevalence by age and by race/ethnicity separately
State Medicaid populations by age and by race/ethnicity separately
National expenditures related to diabetes for a younger and older
adult population from a published study to derive the estimates

Table 22 shows the estimated expenditures They are ballpark estimates of
such spending likely occurring across State Medicaid agencies Figure C1
in Appendix C charts the flow of data, assumptions, and calculations made
to devise the Medicaid spending estimates for diabetes

Although the Medicaid population is primarily women and children, the
diabetes population is disproportionately elderly Data from each source
were reconfigured to reflect the same underlying population and adjusted to
reflect the same year of reference to make data compatible across sources
Because prevalence and cost are so different by age, the estimates were
first generated separately for the adult nonelderly population and the
elderly population and then were reassembled Children and youth under 20
were excluded because
certain pieces of information were unavailable for
them and because prevalence of diabetes type 1 and type 2 among them is
small 025 percent

Another consideration for diabetes is its higher prevalence among certain
racial and ethnic groups Prevalence rates by race/ethnicity were applied
to those respective subgroups of Medicaid Also, Medicaid enrollees of
unknown age or race/ethnicity were distributed in proportion to the known
age or known race/ethnicity subgroups Finally, data from different years
were adjusted to be compatible

The estimates in Table 22 have limitations The obvious limitations in
these estimates include omission of spending for children and the
institutionalized population First, although spending for children and
youth under age 20 is omitted, only 025 percent of this population has
diabetes and the effect is likely to be small Second, the omission of the
institutionalized population is a more serious downward bias on spending
estimates, because people with advanced stages of diabetes are more likely
to be hospitalized or to reside in nursing homes and their care is costly
Third, however, for people dually eligible for Medicaid and Medicare which
is most
of this Medicaid population over 60 years of age, some of the
expenditures for diabetes will be paid for by Medicare and not by Medicaid,
which results in higher estimates here than should be the case The net
effect of these latter two offsetting biases cannot be determined from
these data Fourth, the inclusion of spending for all medical care for
people with diabetes 20 years of age and over is included in these
estimates rather than only the spending related to diabetes because
medical expenditures by type and age could not be identified readily This
overestimates expenditures related to diabetes care The net effect of all
of these limitations is unclear What is clear is that a States Medicaid
data will be a more accurate source for calculating expenses for Medicaid
related to diabetes

One should note that the estimates presented in Table 22 are
approximations to State Medicaid spending on diabetes Estimates
calculated from State Medicaid information systems for diabetes prevalence
and actual Medicaid payments would be more accurate

The estimates here can be useful for understanding the implications of
diabetes for health care costs and the possible returns from investment
in
diabetes care quality States governments eg, State Medicaid Directors
may have actual costs of diabetes for their population If so, then these
actual costs would be preferable to estimates based on national averages
from various data sources Corroboration from external sources can
increase the confidence in State and local estimates based on different
methods
Table 22 Medicaid eligible population and their estimated diabetes
prevalence and expenditures for medical care, for people 20 to 60 and over
60 years of age, 2002

Example Two-Estimates of the cost burden of diabetes for each State: This
example estimates the total cost of diabetes care for each States total
population The total cost of diabetes care includes its direct and
indirect costs Direct costs are directly associated with treatment of the
disease, including medical expenditures for routine services, treatment of
complications, and the increase in general medical conditions attributable
to diabetes Indirect costs are dollar estimates associated with decreased
productivity, disability, and premature death At the end of this section
is an exercise for calculating a States costs with different assumptions
that
might be generated from State data

Table 23 shows estimates of the cost of diabetes for each States total
population using readily available data and following the methods of Hogan,
Dall, and Nikolov 2003 This is a more direct calculation than the
Medicaid calculation because a States total population is more likely to
have characteristics similar to the total US population than is the
Medicaid population

Table 24 is a step-by-step exercise that shows how the estimates were
generated; it provides a guide to States who want to use different
assumptions The data needed include: the size of the State population, the
prevalence of diabetes in the State, and estimates of the cost burden For
the estimates in Table 23, the State populations are from the US Bureau
of the Census see: http://eirecensusgov/popest/data/states/tables/NST-
EST2003-01php State-level diabetes prevalence is available through the
CDC at: http://wwwcdcgov/diabetes/statistics/prev/state/table15htm

The direct and indirect costs of medical care for individuals with and
without diabetes were estimated for the Nation by Hogan, Dall, and Nikolov
2003 Although they used diabetes prevalence estimates from the
National
Health Interview Survey NHIS, the estimates in Table 23 use the CDCs
BRFSS prevalence data because they were available by State Thus, the
estimates of State-level direct and indirect costs when summed across all
States differ slightly from the Hogan and colleagues national estimate of
cost burden

For direct cost per person with diabetes, estimates from Hogan et al are
used Their total direct cost burden per person with diabetes in 2002 is
13,243 The age-adjusted estimate of the direct cost of care per person
without diabetes is 5,642 The 7,601 difference is used in Table 23 to
net out the regular medical care costs for patients with diabetes that is,
cost unrelated to diabetes and its sequelae The 7,601 cost is then
multiplied by the State diabetes prevalence to derive the State estimate
for the direct cost of care for diabetes

For indirect cost per person with diabetes, the Hogan et al estimate
3,289 annually is multiplied by the State diabetes prevalence to derive
the State indirect cost estimate The total cost burden is the sum of the
direct and the indirect diabetes costs for each State

Source for dollar multipliers: Hogan, Dall, and Nikolov 2003

Summary and Synthesis

This module orients users to the importance of data as the foundation of
the quality improvement cycle Data are essential for assessing the
situation and measuring the impact of a quality improvement project
Without it, State leaders could spend effort and resources without
accomplishing the most important goal-improving the health outcomes of
their residents Data, used effectively, should guide the quality
improvement process and enhance a teams effectiveness in focusing on the
right goal and making the right decisions

Module 2 describes two components of data collection for quality
improvement: 1 measurement and 2 data sources The National Healthcare
Quality Report and the National Healthcare Disparities Report now provide
easy access to the health care quality measures and related data sources
that are national and sometimes State-level in scope This module
highlights the diabetes-related measures and data in those reports

Important considerations when using data include data limitations and
making certain that comparison data are truly comparable to the State-level
data Taking an
inventory of existing State and local data sources and
using existing national data and studies can help to fill in gaps in local
data, at least in the planning stages of a quality improvement program

Once data have been identified or collected, the next step is analyzing and
translating those data into information that can be used to make policy-
level decisions Module 3: Information interprets the data from a State
perspective and begins to explore its meaning

Resources for Further Reading

Data and Data Tools on the Internet

Many data resources are available on the Internet, including many sources
used in the NHQR and NHDR Some Web sites allow users to manipulate the
data to produce tables and other useful outputs Such resources include:

HCUPnet
http://wwwahrqgov/hcupnet/

HCUPnet allows users to select national statistics, or detailed
statistics for certain States, for various conditions and procedures
The interactive program also allows users to compare types of patients
and types of hospitals

HCUP User Support HCUP-US
http://wwwhcup-usahrqgov/homejsp

This Web site is designed to answer HCUP-related questions;
provide
detailed information on HCUP databases, tools, and products; and offer
assistance to HCUP users

MEPSnet
http://wwwmepsahrqgov/MEPSNet/IC/MEPSnetICasp

This Web site offers users statistics and trends about health care
expenditures, utilization, and health insurance, including national
and regional health insurance estimates

BRFSS Annual Survey data
http://wwwcdcgov/brfss/technical_infodata/indexhtm

This Web site has detailed technical information about the survey in
addition to downloadable data sets in ASCII and SAS formats

BRFSS
http://wwwcdcgov/brfss/

This Web site provides useful background information about the BRFSS
implementation, technical information, and documentation

DATA2010
http://wondercdcgov/data2010/

This Web site includes data from a number of different State and
national data sources and can be used to monitor the objectives for
Healthy People 2010

Diabetes Registries

Some additional Web sites offer links to useful tools and information to
facilitate data collection at the local level Two Web sites that offer
instruction for
implementing disease registries to track the treatments
received by people with diabetes and other chronic conditions are:

http://wwwhealthdisparitiesnet/training_manuals_and_toolshtml

This Web site, associated with the HRSA Health Disparities
Collaboratives, offers a number of useful tools, including helpful
information for creating and assessing computer registries

http://wwwchcforg/documents/chronicdisease/ComputerizedRegistriesInChroni
cDiseasepdf

This Web site offers a primer on the use of disease registries for a
variety of chronic conditions, including diabetes

Other Useful Web Sites

Associated Appendixes for Use With This Module

Appendix A: Acronyms Used in This Resource Guide

The acronyms employed to describe the organizations endorsing the NHQR
quality measures are described in Appendix A, along with all other acronyms
used throughout this Resource Guide

Appendix B: List of All NHQR Data Sources, Including Those Supporting
State Estimates

Appendix B lists the 25 data sources used in the NHQR and highlights the 10
data sources that provided State-level data in the NHQR

Appendix C: Additional Data Resources Related to Diabetes Care Quality

Appendix C lists additional data resources that may be helpful in studying
diabetes care in a State It includes separate sections, with accompanying
tables, on the NHQR measures selection process see Table C1, details on
data source description and limitations Tables C2-C10, and steps for
estimating Medicaid spending on diabetes care by State Figure C1
Details on notable differences between MEPS and BRFSS national rates are
included, as well as further information on the data sources for
the
process and outcome measures discussed in this module

Module 3: Information - Interpreting State Estimates of Diabetes Quality

Deriving Information From Data

Data do not necessarily convey information Information comes from data
that have been collected, analyzed and arranged to answer a question
Deriving information from data usually requires original data collection
designed to answer the question However, secondary use of data
collected for another purpose can often lead to powerful information,
obtained efficiently

Both original and secondary data collection require strategies for
summarizing and interpreting the results For example, to determine how
well the health care system has educated and motivated people with
diagnosed diabetes to control their blood glucose levels requires original
data collection of HbA1c laboratory values from clinical records The
resulting values of HbA1c levels must be summarized eg, using overall
averages, explored by relevant subgroups eg, managed care versus
private practice to determine how well providers in different settings
educate and motivate their patients, and interpreted in terms of how
well
the assembled database answers the question and represents the total
population eg, data collected from clinical records miss people without
access to health care with undiagnosed diabetes

Secondary data assembled from various sources for the NHQR address the
overarching question of how well the US health care system provides
health care for US residents Although State-specific estimates are
provided in the NHQR for many measures, they are not fully analyzed there
from a State perspective

Steering committees for State quality improvement programs need information
to answer many questions on the States health care quality performance
Among them are:

What measures should the State use to assess health care quality?

What metrics and comparisons for each measure should be used to compare
with the State?

What does the States position among other States mean?

What goals should be set for quality improvement?

While all the questions that a quality improvement committee might raise
will not be answerable from data in the NHQR, it is a valuable source for
identifying readily available and consensus-based measures, for locating
national averages, for deriving other
benchmarks, and for selecting
achievable targets for improvement This module shows how to do these
things from a State viewpoint Module 2 presented a minimum set of
measures from the NHQR that can be used for assessing diabetes quality
within the State Module 3 uses that measure set to describe two steps:

Step 1: Identifying appropriate metrics and comparisons

Step 2: Interpreting the States position among other States

While the specific questions that State leaders ask about the quality of
health care in the State will determine the comparisons to be made, below
is a general guide to thinking about and using the data in the NHQR to
create information for State quality improvement programs

Step 1: Identifying Appropriate Metrics and Comparisons

Benchmark Metrics for States
The NHQR provides a national set of estimates and some State estimates that
can be used as benchmarks for quality improvement A benchmark is an
external marker for assessing how one entity, for example a State,
compares The benchmark can represent the best performer or the average
performer How the State fares depends on what the benchmark is
Several types of metrics or benchmarks can
be used for assessing a State
From more to less stringent, they include:

The theoretic limit of aiming for 100-percent achievement or 0-percent
occurrence for avoidable events, which is an ideal but often impractical
goal

A best-in-class estimate of the top State or top tier of States the top
10 percent of States is used in this Resource Guide, which shows what
has been achieved

A national consensus-based goal, such as Healthy People 2010, set by a
consensus of experts; such goals may be set more or less stringently than
other benchmarks

A national average over all States, which shows the norm of practice
nationwide but, being an average estimate, will represent a weaker goal
than the best-in-class estimate

A regional average, which a State can use to compare itself to other
States that are more likely to face similar environments, but as a goal
it will be less aggressive than the best-in-class goal

An individual State rate, which itself can be used as a baseline against
which to evaluate State-level interventions and progress over time within
the State or to offer as a norm for local provider comparisons

Most of these
benchmarks can be found in or derived from the NHQR The
best-in-class estimate is not reported in the NHQR, nor is the regional
norm based on BRFSS data Both, however, can be derived from data in the
NHQR Detail on how the best-in-class estimate and other benchmarks are
derived is given in Appendix D

These benchmarks for each of the diabetes care-related measures in the NHQR
are reported in Table D1 in Appendix D These benchmarks for four
measures-HbA1c test, eye exam, foot exam, and flu vaccinations-are
graphically displayed in Figure 31

For HbA1c testing, for example, Figure 31 shows a range of benchmark
values Though the theoretic limit may be difficult to achieve for many
valid reasons, the best-in-class estimate has been achieved by some States
The national average is often used to assess a States performance
However, Figure 31 makes it clear that the national average is not a very
difficult level to achieve; about half of the States are above and about
half are below that average The same is true for regional estimates that
take into account the practice patterns in different regions of the
country
Figure 31 Benchmarks of important tests for adults who have
diabetes,
2001

For the eye and foot exam process measures in Figure 31, the best-in-class
average is above the national Healthy People 2010 goal, which itself still
exceeded the national average in 2001 The influenza vaccinations for
adults with diabetes have the lowest rates of these process measures
partially because adults over age 64 are excluded from this measure while
they are included in the other three measures Moreover, Healthy People
2010 did not set a goal for influenza immunization of this population

Understanding State Variation

Although comparing the States rate to a benchmark shows how far or close
the States rate is from the benchmark, it gives few clues as to the
States position among all other States If a States rate is below the
national average, is it the lowest of the low States? Or, is it doing
better than all the other States that are below the national norm? Knowing
this ranking can help a State understand how much effort might be needed to
catch up with health care quality in other States

Average benchmark values do not reveal the degree of variation that exists
on any one measure across the Nation Variation among States can be seen on
a scatter
diagram, where each State represents one point on the graph
Other indicators can be added to and identified on that scatter diagram
with different symbols Figure 32 shows as gray diamonds the
distribution of State rates for important tests that should be performed
each year for people with diabetes It superimposes the national average
as a black square and the best-in-class average as a black triangle

Figure 32 Percent of adults age 18 and over with diabetes who had an
important test at least once in past year, age adjusted, all States and
benchmarks, 2001

Figure 32 reveals that immunization for influenza for people with diabetes
has the most State variation among the four measures and it has the lowest
rates - providers in one State vaccinated only 17 percent of adults aged 18
to 64 with diabetes The spread among the States is nearly fourfold, from
17 to 64 percent Also, the other tests are performed with wide variation
- spread from about 50 percent to 80 or 90 percent of adults with diabetes,
across the States Such variation indicates considerable room for
improvement for many of the States

Figure 32 was modified to track an individual State State A across all
the
measures of diabetes care quality For example, in Figure 33, State A
is represented as a black diamond when it is statistically different from
the national average or as a black-bordered white diamond when it is not
statistically different from the national average

Figure 33 Tracking your State: Percent of adults age 18 and over with
diabetes who had an important test at least once in past year, age
adjusted, for State A, all States, and benchmarks, 2001

The solid black diamond in Figure 33 shows that State As rate compared to
the national average is considered a statistically significant difference
and probably is not attributable to just random variation that appears
among the States and within each State It may well represent some
practice difference in State A that is not common nationally What that
difference is caused by cannot be deciphered from these data Local
insights and exploration are needed to understand underlying factors that
might influence State As rate of HbA1c testing

The black-bordered white diamond in Figure 33 indicates that State As
rate compared to the national average is not considered a statistically
significant difference and could as easily
occur because of random
variation as because of any specific practice by health care providers in
State A Statistical significance and how it is determined is explained
in Appendix E

In general although not shown for all States, here, when individual
States are tracked across diabetes measures, it becomes apparent that there
is uneven performance across measures No single State consistently ranks
highest or lowest across all measures Thus, all States have some room for
improvement compared to national benchmarks and clinical guidelines for the
treatment of people with diabetes

Four States Compared to Benchmarks

To show how States may want to examine their own estimates, four States are
compared to national, regional, and best-in-class State-average benchmarks,
below The national average and best-in-class average, when used together,
summarize key information across the States and enable graphical
comparisons to be simplified as bar charts see Figures 34A-34D

In the bar charts, statistical significance from the national average is
represented by a bold value at the top of the State bar State values that
are not bold are not statistically distinguishable from the
national
average For a discussion of how to consider statistical significance,
see the previous section on Understanding State Variation Also,
statistical tests have been performed to compare the State average to the
best-in-class average These test results are presented in Table 21 in
Module 2: Data

The example States were chosen because each comes from a different region
of the country and, at the same time, they represent a range of experiences
- States performing above or below the national average on individual
measures and States with longstanding and relatively new quality
improvement programs in diabetes prevention and control By using four
States, it is easier to show the nuances of making comparisons with limited
data The graphical and statistical analysis below can be applied to any
State collecting these measures through the BRFSS

Each of these States is described in terms of the four diabetes care
process measures explored generally above Descriptions of their quality
improvement activities can be found in the Module 4: Action

Georgia: Figure 34A reveals two facts about diabetes care in Georgia
compared to national norms:

People with diabetes in Georgia
are more likely than the national norm to
report having had two or more HbA1c test in the past year This is a
statistically significant finding and suggests that Georgia health care
professionals are aware of the importance of glycemic control, are
testing their patients, and may be educating their patients about
glycemic control Whether they are successful in helping their patients
control their blood glucose cannot be determined from these data It is
possible that Georgia physicians see a more advanced stage of diabetes
among their patients and are therefore more concerned about their
patients and are testing them more frequently Special data collection
would be necessary to evaluate the blood glucose levels of people with
diabetes in the State and the effectiveness of the better-than-average
HbA1c testing in Georgia

Georgia does not differ statistically from the national average on the
three process measures that relate to eye exams, foot exams, and
influenza vaccination for adults with diabetes The absence of a
statistically significant difference has to be tempered with the fact
that BRFSS samples for individual States
are often quite small and
probably too small to have the power to detect a difference of the size
measured here, even if it exists Thus, the higher rates of eye exams
statistically insignificant are simply inconclusive When compared to
the more stringent benchmark of the best-in-class rates for these
measures, however, Georgia is not one of the top 10 percent of States
see Table 21 This is especially true for immunization against
influenza where there is almost a 30-percentage-point difference between
Georgias rate and the best-in-class average 30 percent versus 59
percent

Massachusetts: Figure 34B reveals the following about Massachusetts
compared to national norms:

Massachusetts appears to be close to the national average on all of the
NHQR process measures for diabetes care quality, using the test of
statistical significance However, because of the small sample sizes of
the BRFSS, consider the magnitude of the differences from the national
average Massachusetts average for HbA1c testing two or more times per
year is 8 percentage points higher than the average State and for flu
immunizations its average is 7 points higher -
notable differences In
both cases, however, the amount of variation among the States and within
Massachusetts makes these statements equivocal, and the higher values
could as likely be due to chance as to better performance

Massachusetts is not among the top decile States when compared to best-in-
class estimates Massachusetts lower values are statistically different
see Table 21, which means the differences are unlikely to be chance
occurrences compared to the top 10 percent of States This suggests that
Massachusetts may want to focus system-wide efforts on improving diabetes
care quality

Michigan: Figure 34C shows that:

Michigan is similar to the national average across all States for three
of four process measures For HbA1c testing two or more times per year,
and annual eye exams and foot exams, Michigan rates are not statistically
different from the national average and the differences are within 5
percentage points

Michigan is below the best-in-class average Michigan is below the best-
in-class average on all four measures and the differences are
statistically significant Table 21 For two measures in particular,
the
differences are large Rates for HbA1c testing two or more times per
year in Michigan are 27 percentage points lower than the best-in-class
average and rates for influenza immunizations are 32 percentage points
lower This result calls for local study and possibly identifies an
opportunity for Michigan to focus activities more widely on HbA1c testing
and influenza vaccinations for people with diabetes

Washington State: Figure 34D shows the following for Washington:

Washington State performs better than the national average on influenza
immunizations for people with diabetes The Washington rate 496
percent is 12 percentage points higher than the national average, and
the difference is statistically significant Furthermore, although
Washington is not one of the top decile States with values averaging 59
percent and ranging from 56 to 64 percent, Table 21, Washington did
test as not statistically significant from the top decile, given the
amount of variation among and within the States Thus, Washington is
doing relatively well in vaccinating its diabetes population However,
given that rates of immunization are low in all States,
benefits are
possible from activities aimed at improving immunization of people with
diabetes against influenza

Washington is similar to the national average on the other three process
measures Rates for the State are similar to the national average for
HbA1c tests two or more times per year, and annual eye exams, and foot
exams Washingtons rates are higher than, but within 5 percentage
points, of the national average Washington, however, is not among the
top decile States when compared with best-in-class averages see Table
21

Keep in mind that data on diabetes process measures provide a partial
picture of diabetes care in each State Outcome measures would be a
valuable addition for understanding the impact of care processes in each
State The NHQR provided one of its diabetes outcome measures - avoidable
admissions for uncontrolled, uncomplicated diabetes - by 14 States
including the four example States reviewed above These data are discussed
in Step 2
Figure 34A Percent of adults with diabetes, who had an important test
at least once in past year, age adjusted, for Georgia compared to
benchmarks, 2001

Figure 34B Percent of adults with diabetes,
who had an important test
at least once in past year, age adjusted, for Massachusetts compared to
benchmarks, 2001

Figure 34C Percent of adults with diabetes, who had an important test
at least once in past year, age adjusted, for Michigan compared to
benchmarks, 2001

Figure 34D Percent of adults with diabetes, who had an important test
at least once in past year, age adjusted, for Washington State compared to
benchmarks, 2001

Step 2: Interpreting the Data-What Does It Mean?

The data presented in Step 1 raise a number of questions for anyone
involved in quality improvement What does a States position on the
continuum of quality measures mean? What factors influence that position
and the variability among the States? What factors can be controlled
through decisionmaking and local efforts?
Factors That Affect the Quality of Diabetes Care
A number of factors affect the quality and outcomes of health care, as
Figure 35 shows Some factors may be difficult to change, such as
biologically inherited traits; income, education, and social status; and
general population characteristics Others may be changeable in the medium
or long term, but unchangeable in the short term, such
as the supply of
health care professionals, the makeup and mission of health care
organizations, and the disease prevalence of the population which
represents ingrained patterns of personal behaviors and health system
effectiveness or ineffectiveness
Figure 35 Factors That Affect Diabetes Process and Outcome Measures

Although State government and community leaders do not have control over
many of these factors, there are some areas where implementing action at
the State level can increase awareness and promote positive change These
include educating people with diabetes, targeting campaigns about the risks
of obesity and sedentary lifestyles to the general public, raising
awareness among professionals about health care processes that can improve
outcomes for people with diabetes, and creating financial incentives to
encourage providers to improve management of the disease
For example, the CDCs Division of Nutrition and Physical Activity began
funding 20 State programs on prevention of obesity in 2003 These programs
focus on education of people at risk of diabetes and supportive
environments for healthy eating and physical activity Information on
specific State
programs can be found at:
http://wwwcdcgov/nccdphp/dnpa/obesity/state_programs/indexhtm

Other States target minority populations that are disproportionately
affected by diabetes in an effort to affect individual self-management and
other external causes Also, many States have passed legislation to secure
and regulate insurance coverage for people with diabetes because absence of
health care coverage can delay diagnosis, evaluation, education, and proper
monitoring and management of the disease with disastrous consequences see
information at http://wwwncslorg/programs/health/diabeteshtm
To better understand what influences a States position and how it compares
with other States, some factors that are presented in Figure 35 are
discussed in more detail below
Racial, Ethnic, and Socioeconomic Factors: As previously noted, the
socioeconomic makeup of a State will likely play a role in how it compares
to national norms on process and outcome measures States with a higher
proportion of individuals living in poverty, lower average education, and a
more diverse racial and ethnic population, for instance, will likely find
poorer outcomes for their population compared to the national
population
IOM, 2003b

The NHDR AHRQ, 2003b summarizes the racial, ethnic, and socioeconomic
differences in diabetes across the entire Nation, where minority or lower
socioeconomic status is associated with higher diabetes prevalence, higher
diabetes death rates, higher rates of serious complications including end
stage renal disease and amputations Nevertheless, process-of-care
measures generally do not differ greatly among white and minority racial
and ethnic groups at the national level see Table D2, Appendix D
Absence of differences at the national level does not mean that such
differences are nonexistent at the State and local level Outcomes do
differ among racial and income groups at the national level For example,
many more hospitalizations for long-term complications of the disease,
including amputation related to diabetes, are seen for blacks compared to
whites Table D2

The socioeconomic makeup of a State should also play a role in the
strategies that a State uses to improve diabetes care quality For
instance, States may be able to improve diabetes care quality through
efforts targeted at population groups particularly at risk for diabetes
complications The section
on Dissemination: Minority and Rural Outreach
in Module 4: Action describes approaches being used in some States

Biological and Behavioral Factors: The likelihood of developing the most
common form of diabetes, type 2, is influenced by both biology and behavior
National Diabetes Education Program [NDEP], undated [a] Risk factors
for type 2 diabetes include:

Family history of diabetes-Particularly, in the immediate family

Gestational diabetes-Women who develop gestational diabetes during
pregnancy, children whose mother had gestational diabetes while carrying
them NDEP, undated [b], and women who gave birth to at least one baby
weighing nine pounds or more

Age -Risk of diabetes increases with age

Overweight/obesity-A known risk factor for diabetes Overweight is
defined as a body mass index ? 25 23 if Asian American and ? 26 if
Pacific Islander and obesity is a body mass index of ? 30

Lack of exercise -Exercise less than three times a week is associated
with developing diabetes and its future complications

Diet and nutrition-High calorie intake proteins, carbohydrates, or fat
increases the risk of developing diabetes and its
complications

Some additional factors that contribute to developing complications in
people who already have been diagnosed with diabetes include NDEP, undated
[a]:

High blood pressure-Pressure greater than 140/90 mm/Hg is associated with
increased risk of complications for people with diabetes

Abnormal lipid levels-HDL high density lipoprotein, or good
cholesterol less than 40 mg/dL for men and less than 50 mg/dL for women
and triglyceride level greater than or equal to 250 mg/dL are danger
signs of complications for people with diabetes

Socioeconomic factors may be related to underlying biological factors or
behavioral factors The accumulated stress of poverty, low levels of
control in jobs and relationships, low job and life satisfaction, and
societal discrimination against minority groups can influence health status
Williams, 1999

External Environment: In addition to individual characteristics some of
which are amenable to change with personal motivation, each State has
different infrastructure and other environmental factors over which policy-
makers may or may not have control These factors include the collective
health status of the population, the
distribution of health care services
within locales, distribution of wealth and tax resources among communities,
and government programs and leadership

State leaders will face different health care system challenges, including:

Health system infrastructure-Availability of health professionals,
emergency rooms, and hospitals beds

Uninsured populations-The presence of vulnerable and uninsured
populations and the need for special State programs to cover the cost of
health care for them

Safety net infrastructure-The availability of a safety net of health care
providers as a last resort for those who cannot afford health insurance
and private health care

Provider knowledge-Providers who are not up to date with state-of-the-art
knowledge to manage diabetes effectively and of patient education
programs to help patients learn to manage their diabetes

Public education-The need for public education programs that raise
patient awareness of the warning signs of the disease, its potential
complications, the importance of diet and exercise, and the effectiveness
of personal self-management, including knowing when to consult a doctor

Government
resources-The funds, in a time of tight State budgets, to
stimulate quality improvement activities related to diabetes care

Leaders to champion quality improvement- Those leaders who can draw
attention to the problems associated with diabetes and harness the
commitment of health professionals to change practices and monitor
results

Knowledge of what to do-The identification of effective quality
improvement programs that are based on scientific evidence

Adequate data systems to assess progress- Availability of data systems
that can provide comparable comparisons across providers, communities,
and even with other States

The inter-relationship between all of the factors in Figure 35, then,
affects how a State compares with other States on measures of diabetes care
quality It is difficult to measure all of these factors at the State or
local level and to analyze and show their effect with data[1] One
analysis of the NHQR compares hospital admissions for uncomplicated,
uncontrolled diabetes to State environmental factors that are readily
available - measures of poverty, obesity, and diabetes prevalence[2] This
analysis was possible because 14 States in
the Healthcare Cost and
Utilization Project [3] provided their State discharge data for inclusion
in this analysis for the NHQR

Figure 36 shows the resulting associations among admissions for
uncontrolled, uncomplicated diabetes and rates of obesity, poverty, and
diabetes prevalence Diabetes prevalence does not vary much across the
States, but obesity and poverty rates do Admission rates also vary
greatly across these States; most of these State admission rates are
significantly different from the national average, and the low-to-high
rates differ fourfold in magnitude Furthermore, States that have very
high admission rates have higher obesity and poverty rates than the States
with lower admission rates

Yet, as noted earlier in this module, poverty and obesity alone do not
account for all the differences between States in rates of avoidable
hospitalizations for diabetes Other factors certainly play a role The
health system infrastructure, rate of the uninsured, provider knowledge and
incentives, public education, funding and leadership, knowledge of what to
do, and information systems-all will affect the challenges that State
leaders face in leading communities to improve
health care for people with
diabetes

Interpreting Process and Outcome Measures Together

The four States presented earlier in the State-level comparison are
included in Figure 36 Examining these States in terms of process
measures, this one outcome measure, and underlying population
characteristics is instructive
Figure 36

Georgia, which had better HbA1c testing rates for two or more times per
year than the other four States, also has very high rates of avoidable
hospitalizations for uncomplicated, uncontrolled diabetes This suggests
the need to examine the adequate of ambulatory care; perhaps HbA1c
testing is not translating into improved glycemic control for patients
Georgia has one of the highest rates of poverty usually correlated with
lower education among the States; perhaps additional targeted patient
education would be beneficial Furthermore, Georgia ranks third among
States in medically underserved or health personnel shortage areas
Hawkins and Proser, 2004 This suggests that less access to ambulatory
care in some areas may lead to more hospitalizations for early stage
diabetes
Whenever process and outcomes measures do not agree, they
should be examined critically in the context of the State environment

Massachusetts, which had process rates that were not distinguishable
statistically from the national average but that were notably higher on
HbA1c testing rates for two or more times per year and influenza
immunization, has one of the lowest rates of uncontrolled diabetes
hospitalizations among the 14 States Massachusetts population also has
lower rates of the underlying problems of obesity and poverty compared to
other States

Michigan, which had process-of-care rates indistinguishable from the
national average and on the lower end of diabetes care quality, had a
moderately low rate of these avoidable hospitalizations This is despite
the fact that Michigan has a population with high obesity rates but not
high poverty rates

Washington, which had process measures that were fairly similar to the
national average with the exception of its high immunization rate, had
one of the lowest rates of these avoidable hospitalizations
Washingtons population has one of the lowest poverty and obesity rates

These
combined views of diabetes care in the States suggest that the
underlying populations and personal risk behaviors and perhaps self-
management of the disease have more of an effect on the outcomes of care
than whether or not a particular test is given The test itself is not
sufficient for improving diabetes outcomes Complicated interactions of
many factors influence diabetes outcomes Furthermore, often the results
on one measure are not consistent with findings on another measure, even
when the measures are related This indicates the importance of improving
information systems that can track problems and enhance understanding of
the effectiveness of quality improvement programs

None of the above analysis tracks State results with their diabetes care
quality improvement programs No full-scale evaluations have yet been
published of State interventions in health care quality improvement
Through interviews with State officials, this Resource Guide identifies a
few programs that likely have influenced the quality measures discussed
here They are described in detail in Module 4: Action

Summary and Synthesis

This module shows how data from the NHQR can be analyzed and
interpreted to
answer the question of how a State compares to other States and national
benchmarks on health care quality for one disease - diabetes Maps and
charts can be used to help State leaders and quality improvement teams,
whether or not they are trained in statistics and analysis, understand
where their State stands in terms of diabetes quality

A key question for all States is: What goals should the State set as
targets for specific diabetes care quality measures? The NHQR can be used
to identify consensus-based measures, as shown in Module 2: Data States
may identify and define other measures as well The advantage of the NHQR
measures is that the best-in-class State estimate, which can be derived
easily from the NHQR, shows what has already been achieved by some States
It is a reasonable target for most measures However, some measures might
be so crucial to good diabetes outcomes that the target should not be
limited by what other communities have achieved to date Improvements
above and beyond the best-in-class States may be warranted Experts in
diabetes care and local community leaders can help make these types of
judgments

Another key question is: Are all States
able to meet the challenge of the
best-in-class States? The answer depends on the measure, the factors that
relate to that measure health system versus consumer actions, and the
current health and socioeconomic status of the State population The
analyses in this module reveal that many factors influence diabetes care,
making the assessment between diabetes outcomes and processes of care
difficult to affirm Nevertheless, State-level baseline estimates of
diabetes care enable States to assess their starting point and to evaluate
their progress over time

Some States may be able to assemble better data than are available
nationally to understand the quality of care in their State This has been
done in some States see for example Michigan in Module 4: Action State
leaders can assess the quality of diabetes care using the NHQR data to
obtain an idea of where their State stands in comparison to other States
and the Nation One thing is clear from the NHQR data and the information
this module derives from it-no State measures up to all the guidelines for
diabetes care completely The next module provides insights on what
actions some States have taken to improve diabetes
quality

Finally, diabetes is only one of many conditions that warrant improvements
in health care quality While this Resource Guide focuses only on
diabetes, State leaders will ask: What other conditions are ripe for
improvement? The answer will differ by State Tables F1 and F2 in
Appendix F present the quality of care measures for all diseases examined
in the numerous tables of the NHQR by State Thus, assembled in one place,
State leaders can scan the list of measures to see how their own State
compares to the national average across all NHQR measures Once diabetes
quality improvement is on track, State leaders may want to start with
Appendix F to inspire their next campaign to improve health care quality

Associated Appendixes for Use With This Module

Appendix D Benchmarks From the NHQR

Appendix D provides additional detail on benchmarks and how they were
developed and defined for this Resource Guide It also explains the best
benchmarks for stimulating quality improvement This appendix notes that
methods used to generate the benchmarks must be understood to ensure they
are compatible with a States estimates

Appendix E Information on Statistical
Significance

Appendix E shows how to compare State estimates to benchmarks using
statistical significance and p-values that take into account the expected
random variation in estimates This appendix also shows how to calculate p-
values when estimates and standard errors are provided and when estimates,
and thus standard errors, must be derived from the data provided

Appendix F: NHQR Quality Measures for All Conditions by State

Appendix F lists quality measures for all conditions and topics in the
NHQR It includes the national estimate and then an indicator for whether
or not the State estimate not shown due to space limitation is
statistically greater, lower, or no different from the national average
The measures for which State-level data are not reported in the NHQR are
excluded from the table This resource can help State leaders identify
which diseases, in addition to diabetes, are in need of quality
improvement Many of the same data issues related to diabetes are
applicable to other disease topics, although different data sources and
limitations may apply to them

Module 4: Action - Learning From Activities Currently Underway

Discussing the role of State government
in improving diabetes care, Dr
Lawrence Harkless, Chairman of the Texas Diabetes Council, had advice for
State leaders interested in diabetes quality improvement Poor quality
diabetes care is not about bad people, its about bad systems In the
fifteen minutes a doctor has with a patient, he/she will address the most
pressing health concerns So many of these patients have multiple
conditions that create competing priorities for doctors

Until research provides a cure for diabetes, constant efforts to
increase awareness, knowledge and skills - in our health sciences
schools, our private and community health centers, our schools and our
local and State government - are crucial to our success in controlling
this destructive disease, he added The economic costs from lost
productivity, the health care costs of life-threatening complications,
and the personal costs of limited fulfillment - these are costs our State
can ill afford to pay

- Dr Lawrence Harkless, Chairman of the Texas Diabetes Council,
and Professor, Department of Orthopedic Surgery, and Louis Bogey
Professor of Podiatric Medicine and Surgery, University of
Texas
Health Sciences, San Antonio, Texas

In Module 1: Background, readers had the opportunity to learn about
diabetes, its consequences in terms of cost and its toll on human life, and
the need for quality improvement in health care, particularly as it relates
to diabetes Module 2: Data introduced readers to data from the NHQR and
how these data can be useful to States Module 3: Information demonstrated
how State leaders could use data to make accurate comparisons and
assessments of diabetes care quality in their States This module will
examine various models of quality improvement, ranging from private
efforts, not directly related to government, to Federal, State, and local
government initiatives

Within health care, many organizations and individuals play a role in
efforts to improve quality Rather than reinvent the wheel, State leaders
have the opportunity to learn and draw lessons from initiatives that are
ongoing at both the national and State levels in both the public and
private arenas These initiatives also have publications, guidelines, and
other resources that can assist the development of new initiatives Listed
below are selected
programs that are central to States and their ongoing
diabetes quality improvement efforts Appendix G gives a more extensive
listing of various diabetes quality improvement efforts involving national
non-governmental organizations and Federal agencies with Internet links for
more information for State leaders

Selected Public/Private Quality Improvement Initiatives

There are a wide range of public and private quality improvement
initiatives active at different stages of quality improvement Although
the components of quality improvement are numerous, the examples given
below illustrate the action at stages most important for State leaders,
including the collection of measurement data and the implementation of
quality improvement programs Some organizations focus on one stage of
quality improvement while many play a part at all stages This list is by
no means exhaustive, but it provides examples of how national organizations
and partnerships are related to State efforts These strategies are being
widely implemented and fine tuned for various populations and
organizations

National Diabetes Quality Improvement Alliance

One of the most important advances in quality improvement
is the
development of the consensus-based measures to assess health care quality
Organized by leading diabetes stakeholder groups in 1998, the Diabetes
Quality Improvement Project DQIP was a voluntary coalition of public and
private organizations that have cooperated to develop a national set of
diabetes-specific performance and outcome measures Comprised of the
American Diabetes Association, the Centers for Medicare Medicaid Services
CMS, the Foundation for Accountability, the National Committee for
Quality Assurance, the American Academy of Family Physicians, the American
College of Physicians, and the Department of Veterans Affairs, DQIP was the
first successful collaboration to develop a single set of performance
measures to determine the appropriateness and effectiveness of diabetes
care The data collected included measures for HbA1c, blood pressure, lipid
profiles, eye and foot exams, and smoking cessation counseling, among
others

In 2001, the DQIP partners joined other leading organizations, including
the American Medical Association and the Joint Commission on Accreditation
of Healthcare Organizations, to form the National Diabetes Quality
Improvement Alliance NDQIA The
Alliance agreed to work on developing
one national performance measurement set for diabetes accepted by all major
stakeholders In October 2002, the newly formed Alliance developed
national, uniform consensus standards from all parties - purchaser,
provider, and consumer groups The NHQR includes a subset of these
measures for which national data exist Some States have used the DQIP and
NDQIA measures as the basis for developing local diabetes guidelines and
reporting Further information on the Alliance and its national measures is
available at http://wwwnationaldiabetesallianceorg/
The Chronic Care Model

One model of quality improvement particularly applicable to diabetes care
quality in the clinical setting is the Chronic Care Model Dr Edward
Wagner and his team at Group Health Cooperative in Seattle, with support
from the Robert Wood Johnson Foundation, developed the Chronic Care Model
The US health care system is oriented more toward care for acute episodes
of disease rather than prevention and management of chronic conditions
Thus, the Chronic Care Model emphasizes a collaborative approach among
health care teams to develop new and better clinical procedures and systems
that
support providers and patients in treating and managing chronic
illness over time More information is provided below on involvement of
State health departments in Diabetes Collaboratives that use the Chronic
Care Model to achieve rapid advancement in diabetes care at community
health centers More information on the Chronic Care Model is available on
the Improving Chronic Illness Care ICIC Web site at:
http://improvingchroniccareorg

IHI Breakthrough Series Collaboratives

The Institute for Healthcare Improvement IHI created the Breakthrough
Series Collaboratives to assist health care organizations with making rapid
advances in lowering costs and improving quality for a variety of
conditions in a variety of health care settings A collaborative brings
together quality improvement experts and practice teams from many different
health care organizations that work together for 6 to 8 months to achieve
quality improvement in a specific area Since 1995 when IHI held the first
Collaborative, more than 700 trained teams from over 450 US and Canadian
health care organizations have participated in these programs By
capitalizing on the collective wisdom of participating
organizations,
expert faculty, and improvement advisors, these organizations have
dramatically improved outcomes and reduced costs in a variety of areas,
including:

Reduced waste in the form of shorter intensive care unit stays and less
waiting time

Dramatic reductions in defects such as adverse drug events, long waits
for pain medications, and unnecessary hospitalizations for chronic
conditions

New levels of performance achieved including enhanced control of blood
sugar and access to primary care

IHI combined efforts with the Group Health Cooperatives Improving Chronic
Illness Care program to train health care providers and others in using the
Chronic Care Model to accomplish real change in the way chronic diseases,
including diabetes, are treated and tracked Institute for Healthcare
Improvement, 2002 Hundreds of health care teams around the country are
currently using the Breakthrough approach combined with the Chronic Care
Model in Health Disparities Collaboratives sponsored by HRSAs Bureau of
Primary Health Care Health Disparities Collaboratives are discussed in
further detail later in this module The short-term evaluations of
Collaboratives showed
improvements in blood sugar control for diabetes
patients; dramatic increase in followup for patients with depression;
decreased rates of blood pressure among patients with cardiovascular
disease; success in providing asthmatic patients with daily preventive
medicines; and decreasing health care costs even while increasing the
number of patient visits Wagner, Austin, Davis, et al, 2001 More
information about IHI, its Breakthrough Series, and diabetes programs can
be found on the following Web sites:

Breakthrough Collaboratives general information:
http://wwwihiorg/IHI/Programs/CollaborativeLearning/

Improving care for people with chronic conditions - diabetes:

http://wwwihiorg/IHI/Topics/ChronicConditions/Diabetes/HowToImprov
e/

Report from the Health Disparities Collaborative on Diabetes:
http://wwwhealthdisparitiesnet/Diabetes_Apr2002pdf

Other Strategies

Self-Management Programs

Diabetes is one chronic condition whose treatment and outcomes are heavily
dependent on how well the patient monitors and manages the disease outside
the health care setting An important approach to quality improvement for
diabetes is
improving patient self-management Self-management programs
emphasize and focus on patient education and behavior modification Health
care professionals work with patients to build their confidence in managing
their own disease, in working within the health care system and the
community to have their needs met, and in managing the emotional effects of
their illness Patients are informed about their disease and trained using
evidence-based information in how they should manage their condition A
variety of educational tools are used to assist the patient for example,
classes, Internet information, and toll-free hotlines There are national
standards for diabetes self-management and patient education Because of
the critical role of patient self-management in diabetes care, some
purchasers are beginning to provide reimbursement for certified diabetes
educators to interact with diabetes patients

One AHRQ-sponsored study conducted by Stanford University researchers
showed that 2 years after participating in a self-management program, study
participants showed reductions in health distress, made fewer visits to the
doctors office and emergency room, had not experienced any
further
increases in disability, and had increased self-efficacy Lorig, Ritter,
Stewart, et al, 2001 More information on the Chronic Disease Self-
management Program at Stanford University is available at:
http://patienteducationstanfordedu/programs/

Disease Management Programs

Another model for quality improvement that is capturing attention
nationwide is disease management Disease management is a term that refers
to a variety of programs and interventions that seek to:

Identify patients with a particular chronic condition or set of
conditions

Establish a coordinated system of interventions and information-sharing
for enrolled patients and their providers

Encourage doctors and other health care providers to use evidence-based
practice guidelines to treat chronic illnesses

Educate and train patients in self-management so that they avoid disease
complications

Monitor interventions and outcomes over time to evaluate the
effectiveness of the disease management program

Disease management has grown rapidly over the past five years and is now
used widely by employer-sponsored health plans to manage costs and improve
clinical care for many chronic
conditions, including diabetes More
recently, State Medicaid programs and Medicare also have begun to use
disease management for their populations Initial assessments from State
Medicaid disease management programs are promising in terms of cost control
and quality improvement Brown and Matthews, 2003; Wagner, Austin, Davis,
et al, 2001; AAHP/HIAA, 2003 Table 41 below lists Medicaid diabetes
disease management efforts that are underway More information on disease
management programs in general is available from the Disease Management
Association of Americas Web site at http://wwwdmaaorg Further
information on diabetes disease management programs is available at the
Council of State Governments CSG Web site at
http://wwwcsgorg/CSG/Policy/health/chronicillness/defaulthtm

Selected Federal Programs and Resources for Diabetes Care Quality
Improvement

In addition to public/private quality improvement efforts, State diabetes
efforts are also linked with Federal programs There are a variety of
programs at the Federal level that address diabetes and quality
improvement; some of these are partnering with States, and others have
useful resources for State efforts

CDCs Diabetes
Prevention and Control Program

The Centers for Disease Control and Prevention currently helps to fund the
Diabetes Prevention and Control Program DPCP in every State The DPCP
model began as a small number of demonstration projects in the late 1970s
In response to the growing burden of diabetes in the United States, the
program has evolved into a nationwide, joint State-Federal effort with the
CDC spending 20 million annually throughout the 50 States, the District of
Columbia, and 8 US territories and island jurisdictions These programs
and the people who staff them are rich information resources on diabetes
See http://wwwcdcgov/diabetes/states/indexhtm for links to each State
DPCP

Source: The Council of State Governments CSG This table is derived from
a review of State and Federal Web sites and published literature on
Medicaid disease management by CSG staff Published source material
included Brown and Matthews, 2003; Wheatley, 2001; Faulkner, 2003; NCSL,
2003, US Department of Health and Human Services, 2003b

The CDCs DPCP has developed two types of programs: capacity building and
basic implementation Twenty-six States currently have capacity building
grants with an average award of 270,000 to:

Develop initial expertise in diabetes control

Provide a focal point for diabetes control

Establish systems to define the scope of the diabetes problem

Identify gaps in diabetes care, for both patient access and quality-of-
care issues

Develop and evaluate limited intervention projects

Identify external supporters for diabetes control activities

DPCPs basic implementation program awards an average of 725,000 to State
health departments Twenty-four States currently have basic implementation
grants The implementation grants are to:

Build on expertise in program, science, and
policy areas to control and
prevent diabetes

Coordinate statewide diabetes control and prevention

Expand systems to define and analyze the scope of the diabetes problem

Improve access to diabetes care for all people and raise the quality of
that care

Use statewide public health projects to reduce diabetes-related problems

Inform, educate, and empower external supporters to control and prevent
diabetes

To qualify for CDC funds, State governments are required to provide
matching support through State funds or in-kind commitments of personnel or
other resources The amount of State funding varies Some States provide a
significant level of their own funding for diabetes efforts, surpassing CDC
funding by two or three times Texas, for example, appropriated more than
6 million in State funding for diabetes in fiscal year 2003-2004 Other
States provide more modest support or no additional support In addition,
money is often provided through private grants States with higher
incidence of diabetes also do not necessarily spend more on their diabetes
prevention and control programs CDC aims to assist State health
departments in developing programs to address
the disease; CDC funding
amounts to approximately 127 per American with diabetes see Appendix H
for a breakdown of CDC and State DPCP funding for all 50 States

In 1999, the CDC required each State to establish measurement and
evaluation procedures to track and promote program success DPCP uses a
model of influence approach As such, the DPCP acts as a mechanism for
improving diabetes care through strategic partnering and programmatic
interventions The purpose is to ultimately affect broad change in the
health system and the health of the community The evaluation and
accountability requirements are meant to stimulate such activity on the
part of the DPCP Safran, Mukhtar, Murphy, 2003 The evaluation framework
of this policy shift is detailed in the discussion on evaluation in Module
5: Improvement
Diabetes Detection Initiative and Steps to a HealthierUS

Under the leadership of Secretary Tommy G Thompson, the US Department of
Health and Human Services has developed a new initiative, the Diabetes
Detection Initiative: Finding the Undiagnosed More than 5 million of the
182 million people with diabetes in the United States do not know they
have the disease The Diabetes Detection
Initiative DDI is a community-
based effort to identify individuals with type 2 diabetes who have not been
diagnosed The DDI is designed to raise awareness of diabetes risk
factors, increase blood testing of individuals at risk for diabetes, and
increase diagnosis and treatment for those people who do not know they have
the condition

Ten communities around the Nation with high risk populations are serving as
DDI pilot sites, including Oakland, California; Wichita and Sedgwick
County, Kansas; Springfield/Holyoke, Massachusetts; Flint, Michigan; East
Harlem, New York, Choctaw Nation, Oklahoma; Orangeburg County, South
Carolina; Seattle, Washington; Fayette and Greenbrier Counties, West
Virginia; and Wind River Indian Reservation, Wyoming Future plans calls
for the DDI to expand to other locations across the country The Diabetes
Detection Initiative is aligned with other Federal health initiatives,
including the Secretarys Steps to a HealthierUS and the Presidents
HealthierUS programs, which are aimed at encouraging physical activity,
improved nutrition, and a more prevention-oriented society More
information on the DDI is available at http://wwwndepnihgov/ddi;
additional
information on Steps to a HealthierUS is available at
http://wwwhealthierusgov/steps/indexhtml

HRSAs Health Disparities Collaboratives

HRSAs Bureau of Primary Heath Care BPHC and the CDCs Diabetes
Prevention and Control Program sponsor Health Disparities Collaboratives, a
unique partnership with community health centers CHCs across the country
aimed at improving chronic illness care for underserved and minority
communities CHCs are the key safety net providers for low-income,
uninsured patients throughout the country The low-income and ethnically
and racially diverse populations at community health centers have an
increased risk of complications from chronic illness NACHC, 2003 In an
ambitious program to reduce health disparities, HRSA began the first
Diabetes Collaborative in 1999 with 85 CHCs The CHCs developed registries
and enrolled 16,000 people with diabetes in the collaboratives In 2000,
another 120 health centers participated in a second Diabetes Collaborative

The Health Disparities Collaboratives incorporate the change model created
by the IHI Breakthrough Series and the Chronic Care Model for diabetes care
improvement This program has allowed CHCs to participate in
team training
to apply best practice models of care for chronic disease The population-
based model of care relies on identifying which patients have an illness
and ensuring that they receive evidence-based care The model helps
patients to participate and manage their conditions Over the course of
the 1-year collaborative, the CHC teams participate in learning sessions
and set goals, such as data collection on certain outcomes for example,
blood tests Then they develop, test, and implement evidence-based
strategies for a specific clinical area for example, diabetes and for a
specific community Between meetings, CHC teams focus on implementing
goals and measuring changes in their health centers The team collects
data to measure the impact of the changes and additional learning
opportunities allow teams to improve processes over time The teams share
information and learn from national experts and each other through a
Listserv, regular site visits, monthly progress reports, and conference
calls Results indicate the rate of HbA1c testing for people with diabetes
increased significantly at the participating centers over the first year
Health Disparities Collaborative,
2004

Additional information on the Bureau of Primary Care and the Health
Disparities Collaboratives is available at
http://bphchrsagov/programs/HDCProgramInfohtm and
http://wwwhealthdisparitiesnet/

National Diabetes Education Program

The National Diabetes Education Program NDEP is a national collaboration
sponsored jointly by the National Institutes of Health NIH and the CDC
The NDEP includes over 200 partners at all levels of government and
society Many State DPCPs use NDEP materials and partner on NDEP
initiatives The goal of the NDEP program is to improve prevention and
treatment of diabetes, thereby reducing illness and death from this
disease Because so many of the complications from diabetes are
preventable, the NDEP seeks to help educate the public about diabetes,
promote better patient self-management, improve the quality of care for
diabetes, address health policies that may improve quality and access to
care, and reduce disparities among racial and ethnic populations that are
disproportionately affected by diabetes A variety of resources on
diabetes quality of care improvement as well as education and awareness
campaigns and other resources are available at the NDEP
Web site at
http://ndepnihgov Another part of the NDEP is a Web site devoted to
improving diabetes care at http://wwwbetterdiabetescareorg The site has
information, resources and tools for providers, educators, and
organizations on how to participate in and advance quality improvement in
diabetes care

CMS Quality Improvement Organizations

Under Titles 11 and 18 of the Social Security Act, Quality Improvement
Organizations QIOs are designated as the guardians of quality, cost-
effective care for both Medicare and Medicaid The 37 QIOs in the United
States, also known as peer review organizations, are non-profit
organizations that operate under the direction of the Centers for Medicare
Medicaid Services QIOs are responsible for using medical reviews, data
collection and analysis, and other functions authorized by CMS as a means
to achieve national, State, and local quality improvement goals QIOs are
vital partners in CMS Health Care Quality Improvement Program due to their
collaborative relationships with local networks of hospitals and providers
QIOs have been involved in several State and local quality improvement
projects related to diabetes Qualis, a QIO in Washington
State, was a
partner with the Washington State Department of Health and the Improving
Chronic Illness Care program of the Robert Wood Johnson Foundation in the
Washington State Diabetes Collaborative Missouris QIO, MissouriPRO,
participated in the HRSA Health Disparities Collaborative for diabetes in
community health centers in the State North Dakotas QIO has assisted
clinics with implementing diabetes flow sheets, increasing preventive care
and screening and establishing a diabetes care tracking system that
generates reminders for routine diabetes checks General information on
the role of QIOs is available at http://wwwcmshhsgov/qio/ Specific
information on QIO diabetes quality improvement initiatives is available at
http://wwwmedqicorg/content/nationalpriorities/topics/projectdesjsp?topic
ID477showMeasuresyesshowStepsyes Examples of QIO initiatives in
various States are available on the American Health Quality Association Web
site at http://wwwahqaorg/pub/quality/161_689_2974cfm

State Approaches to Diabetes Care Quality Improvement

The following sections summarize various kinds of State diabetes quality
improvement approaches relating to partnership/planning activities,
program
development, and dissemination A few States are highlighted under each
type of approach to illustrate examples of best practices

States have undertaken a variety of diabetes initiatives over the years,
most of which have been spearheaded by State DPCPs Although the mandate
of State DPCPs covers many aspects of diabetes prevention and control,
States DPCPs have included quality improvement as a part of their diabetes
work States have used CDC funding to establish creative programs to
address diabetes quality improvement, ranging from using the Chronic Care
Model in collaboratives to developing diabetes guidelines

There are also stand-alone State initiatives that are not directly
connected to CDC and State DPCP efforts States have established diabetes
disease management programs in Medicaid and have partnered with the private
sector on quality improvement related to diabetes Many States have also
tried to integrate CDC-funded efforts with private-sector and Medicaid
efforts

The range of State activities makes it difficult to present all of the
possibilities Instead, various activities and programs States have used
to address diabetes care quality are listed below
Except where other
citations are provided, the information provided below was derived from a
review of State health department Web sites, CDC resources, Internet
research, and in-person interviews with State agency officials A focus
group of State officials and diabetes experts also assisted with
formulating the categories for State diabetes quality improvement
approaches State examples were selected in order to provide a sampling of
State efforts that reflects regional, size and funding differences between
States Also, the uniqueness of the State efforts in relation to similar
programs was taken into consideration Although not an exhaustive list, it
demonstrates a range of efforts States have undertaken related to diabetes
quality improvement These efforts may be cataloged as follows:

Partnership/Planning Activities
Coalitions
Advisory bodies and councils
Working across State agency lines

Program Development
Developing and complying with diabetes guidelines
Data measurement and reporting
Use of technology
Self-management/patient education
Collaboratives
Provider training

State disease management programs

Dissemination
Raising awareness through public relations
Minority and rural outreach

Partnership/Planning Activities

Coalitions

Creating networks of support has been critical for States that have
established far reaching programs addressing diabetes quality improvement
Coalitions bring together a broad variety of stakeholders in a State to
work together to identify areas of strength, common objectives, and gaps in
service They also develop plans to assure that the essential treatment
and educational services for managing diabetes are in place in a community
Coalitions also include community representatives and nontraditional
partners such as the corner grocery store owner, faith communities, health
organizations, social service agencies, and more Coalitions can develop
strategic nontraditional plans and establish measures and processes for
determining community success
Californias Diabetes Coalition, which includes representatives from the
general public, the State DPCP, local health departments, universities,
volunteer organizations, pharmaceutical companies, and community-based
organizations,
has developed evidence-based guidelines, a patient survey,
and a model patient record
Advisory Bodies and Councils

A number of States also have advisory boards and councils that assist with
statewide diabetes planning and quality improvement efforts Whereas
coalitions are broad-based, voluntary efforts, advisory bodies are usually
smaller, more formalized entities with objectives and structure that are
established by law Advisory bodies and councils include a variety of
experts and stakeholder groups such as the American Diabetes Association,
State professional associations, and provider organizations, among others

Floridas Diabetes Advisory Council advises the Governor and the
Secretary of the Department of Health on emerging diabetes issues
affecting care, treatment, and quality of life

The Texas Diabetes Council was created by the Texas legislature in 1983
to promote diabetes prevention and awareness, to work with private and
public health care organizations, and advise the legislature on laws
needed to further education and health services for people with diabetes

Working Across State Agency Lines

State programs often operate in isolation
from one another However,
several States have recognized that their diabetes prevention and control
program can work with other agencies within State government to reduce
diabetes and its complications This approach can be highly efficient and
effective in reaching targeted groups for prevention and disease
management

Marylands Medicaid program adapted the Maryland DPCPs Model for
Comprehensive Diabetes Management, paying for a package of preventive
services, equipment, and supplies for diabetes care Although the program
was later handed over to Medicaid managed health plans, an independent
evaluation found that the diabetes care program saved an average of
almost 4,600 a year per program participant

Massachusetts Diabetes Program partnered with the Division of Medical
Assistance to implement a patient education and provider training
initiative incorporating the Massachusetts Guidelines for Adult Diabetes
Care This involved quality improvement and measurement initiatives
related to health outcomes for people with diabetes

California worked with the training division of the Department of Motor
Vehicles to educate officers in evaluating
people who come to the
departments attention due to diabetes

West Virginias DPCP has established a worksite health promotion program
for State employees that facilitates lifestyle changes to improve the
health and self-care practices of people with diabetes

Program Development Activities

Developing and Complying With Diabetes Guidelines

To close the gap between research and practice, several States are
promoting the use of evidence-based clinical guidelines for diabetes care
Many States have adopted existing guidelines established by the National
Quality Forum, HEDIS Comprehensive Diabetes Care Measures or the American
Diabetes Association, while others have worked through the process of
developing their own

Massachusetts DPCP convened a Diabetes Guidelines Work Group to develop
the Massachusetts Guidelines for Adult Diabetes Care and accompanying
tools for primary care settings

Nebraskas Medicaid program has established a Diabetes Subcommittee that
is developing consensus guidelines and working with health plans and
providers to ensure implementation of the guidelines among those covered
by Medicaid

Data Measurement and Reporting

As Module 2:
Data indicated earlier, data measurement and analysis is a
fundamental step in quality improvement State DPCP and others
organizations have come together to agree on consensus measures on diabetes
quality and used the data to compare quality performance among health plans
and providers

Michigans DPCP established its Diabetes Core Measures Initiative in
collaboration with the Michigan Associate of Health Plans The measures
were developed to ensure that all patients with diabetes receive
evidenced-based care

The New Jersey DPCP developed and implemented diabetes care performance
measures and integrated them into routine clinical practice in several
managed care and community health care settings The performance
measures are published in a State newsletter and on the Internet at
http://wwwstatenjus/health/fhs/diabnewshtm

Use of Technology

States are taking advantage of new technologies to improve diabetes care
through better communication and more efficient services

California created a series of electronic seminars on diabetes-related
issues for DPCPs around the country and coalition members throughout the
State

Maines Consortium for
Clinical Office System Improvement has worked to
implement an array of tools for primary care practices aimed at quality
improvement, prevention and chronic disease management, including the
Cardiovascular Diabetes Electronic Management System

Oklahoma partnered with the University of Oklahomas Ophthalmology
Department to enable rural Oklahomans to receive diabetic retinopathy
screening in their own communities using a state-of-the-art fiber optic
telemedicine design

Self-Management/Patient Education

Patient self-management is critical for good diabetes outcomes Several
States have established certification programs for diabetes self-management
educators By requiring this training, States can set a high standard
based on the latest evidence-based information Patient education programs
are best conducted in a variety of settings that are easily accessible to
target populations, including: churches, neighborhood associations, and
other community-based organizations that are well recognized in a
community These programs can be conducted in small groups or one-on-one,
based on the identified needs of the population For more information on
diabetes education
programs, visit the ADAs Web site at
http://wwwdiabetesorg/education/edustate2asp

Rhode Island created a statewide initiative called My Diabetes Record,
which is aimed at improving self-management of diabetes and meeting the
national HP2010 objectives for eye care, foot care, HbA1c tests, lipid
profiles, and influenza and pneumonia vaccinations All third-party
insurers use this standard tool

Utahs DPCP has a State-sponsored certification process for outpatient
diabetes self-management programs The voluntary program uses national
guidelines and evaluates diabetes clinical quality improvement

Arkansas Medicaid and DPCP have partnered with the Eli Lilly and Company
to provide diabetes self-management education in underserved areas of the
State

Collaboratives

Improving the quality of care for diabetes is a systemic issue The entire
health care system and all its actors need to be mobilized to deal with
diabetes Thus, a number of States established their own statewide
collaboratives or have worked with community health centers on the HRSA
Health Disparities Collaboratives to achieve diabetes quality improvement

New Mexico was one of several
States to participate in the first HRSA
Health Disparities Collaborative focused on diabetes Eleven clinics or
practices participated and used an electronic diabetes patient registry
to ensure people with diabetes received recommended care with the State
health department serving as technical advisor to the participants

The State of Washington leads the way in establishing State-based
diabetes collaboratives Since 1999, Washingtons three diabetes
collaboratives have reached 65 clinical practice teams and accomplished
significant clinical improvements, such as reductions in HbA1c levels,
cholesterol, and blood pressure There was also improvement of 35-50
percent in the number of patients who received foot examinations, blood
pressure screenings, and cholesterol tests Daniel, Norman, Davis, et
al, 2004

Wisconsin developed a unique public-private initiative in conjunction
with managed care plans in the State The Wisconsin Collaborative
Diabetes Quality Improvement Project monitors and evaluates plan
performance on diabetes measures and works together on quality
improvement initiatives More in-depth information about this
initiative
is provided in Module 5: Improvement

Provider Training

Because health care providers are a key element in improving diabetes
quality care, many States have actively sought their involvement in
developing programs In addition, States are providing outreach and
support to health care professionals as they seek to implement new evidence-
based care guidelines

New York established three diabetes centers of excellence Medical
centers in the State competed for the recognition and additional funding
available for the designated centers of excellence The centers conduct
research and provide health care professionals, providers, and patients
with information and resources aimed at improving diabetes prevention and
treatment Cornell, 2003

New Hampshire offers an annual statewide multi-track professional
training conference targeted to primary care health care professionals,
insurers, legislators, podiatrists, school nurses, occupational health
nurses, and other health and human service professionals

North Carolina provides scholarships for local health department staff to
attend the East Carolina University School of Medicines Clinical

Fellowship in Diabetes The week-long continuing education program is
led by a diverse group of faculty who address everything from quality
clinical care for diabetes patients to increasing the cultural
competencies of providers The health care professionals who attend are
then required to train colleagues in their local communities

State Disease Management Programs

Because States are looking for ways to control costs while maintaining or
improving quality in Medicaid, more than 20 States are implementing disease
management programs, many of them targeting diabetes Smith, Ellis,
Gifford, et al, 2002; see table 41 below Medicaid disease management
programs seek to increase patient knowledge and self-management skills,
improve provider adherence to clinical guidelines, and implement technology
to track patients more effectively Improved care management for diabetes
is aimed at decreasing preventable complications, thereby controlling costs
and potentially improving long term health outcomes

Floridas Disease Management Initiative has the longest running Medicaid
disease management program in the Nation, addressing a variety of chronic
illnesses, including
diabetes Brown and Matthews, 2003

Indiana launched the Coordinated Care Management program, a voluntary
disease management program for Medicaid patients with diabetes, chronic
heart failure, asthma, and other costly conditions for Medicaid The
program will hire 80 new nurse managers over a 2-year period to perform
assessments and conduct patient education US Department of Health and
Human Services, 2003

Kentuckys Medicaid Managed Care plan, Passport, identifies members with
diabetes through claim review, the nurse advice line, and referrals from
doctors The plan uses patient education and provider interventions to
improve self-management and compliance with treatment guidelines Since
its inception in 1999, enrollees are doing better than the national
average in monitoring symptoms and controlling the disease, and patient
adherence and performance has improved each year of the program Atkins,
2003

Dissemination Activities

Raising Awareness Through Public Relations

An important component of addressing diabetes care involves raising
awareness Surprisingly, while there are 13 million diagnosed cases of
diabetes in the US in 2002, there
were 52 million undiagnosed cases of
diabetes CDC, 2003c If the diabetes goes too long without proper
diagnosis, lasting damage to an individuals health can occur Thus, it is
important that the general public and providers be aware of the disease and
its symptoms States use a variety of methods to spread the word about
diabetes

Wyomings DPCP published a brochure, What Wyoming Should Know about
Diabetes, and distributed it to 21,000 Medicaid-eligible households and
to more than 50,000 other citizens

Tennessees DPCP collaborated with the ADA, the Tennessee Academy of
Ophthalmology, and the University of Tennessee Agricultural Extension
Service to bring the National Eye Institutes traveling vision exhibit to
Tennessee

Minority and Rural Outreach

The prevalence of type 2 diabetes is increasing most rapidly among minority
populations In addition, millions of people living in rural area have
diabetes, and special attention must be given to ensure they are receiving
quality health care The NHDR reveals that minority racial/ethnic groups
and lower socioeconomic groups receive fewer services for diabetes care,
and that African Americans and Hispanics have higher
hospitalization rates
for complications of diabetes AHRQ, 2003b

Several States have developed innovative programs to target these groups
A first step in addressing this concern is making patient information
available in an understandable format This could involve using pictorial
representations or providing documents in languages other than English
Reaching these groups also involves tailoring the message or targeting the
delivery

Removing the Language Barrier

Florida has made their entire DPCP Web site available in Spanish

Washington has 20 self-management educators who are specially
trained in delivering diabetes programs in Spanish

Targeting the Message

North Carolina partnered with the General Baptist State Convention
and the States Office of Minority Health, to conduct programs for
African American congregations throughout the State that focus on
awareness, risk factors, complications, and prevention strategies
The program provides educational presentations, workshops, and
materials and develops public service announcements to radio
stations with a predominantly African American
listening audience

Minnesotas DPCP coordinates with the Office of Minority Health to
address diabetes among minorities Funds earmarked for reducing
disparities in the minority and Native American population pay the
salaries of two staff members who work on diabetes efforts targeted
at these groups

Rural Outreach Efforts

Colorado implemented the Rural Diabetes Project that promotes
diabetes preventive practices through a tracking and followup
system with private eye care and primary care providers for eye
disease screening and blood pressure control Colorado also
coordinates the Buddy System, a network of health professionals
that provide diabetes education in hospitals, clinics, and public
health agencies Rural educators are matched with certified
diabetes educators for one-on-one consultations

Profiles of Selected Best Practice States

This section examines the mix of programs that four different States DPCPs
use to improve diabetes care quality The States profiled here were
selected based on a variety of criteria A list of high-performing States
was developed based on
rankings in the NHQR on diabetes care quality This
list was supplemented by information on best practices from the CDC, the
Assistant Surgeon Generals office, and research on other innovative
diabetes quality improvement programs From this list a cross section of
States was selected that represented different areas of the country,
geographic and population differences, and baselines for diabetes care
quality Some the States listed below score well on diabetes quality of
care measures in the NHQR Others are below national averages according to
NHQR data Thus, these States demonstrate real-world approaches to
improving diabetes care that attempt to surmount the challenges that States
face

California

California uses a variety of approaches and partnerships to address
diabetes in the State The States Medicaid program, MediCal, identified
diabetes as a high-cost disease The DPCP investigated the effect of case
management on the Medicaid population The 4-year study showed that case
management resulted in a significant reduction in HbA1c levels California
Medi-Cal Type 2 Diabetes Study Group, 2004 Now that the DPCP has shown
that this strategy works, it is working on funding for
a study that will
help determine whether this effort would be cost effective and feasible
throughout the Medicaid population

The California Cooperative Healthcare Reporting Initiative CCHRI is an
innovative public-private partnership that has developed a program for
measuring diabetes quality of care see box below California is part of
the HRSA Health Disparities Collaborative which works with community
clinics on diabetes care The California Primary Care Association expanded
the program to include more clinics with the funding support of the
California Health Care Foundation California is also one of five States
involved in the HRSA sponsored diabetes collaboratives that focused on
identifying pre-diabetes California also uses NDEP educational materials
and is participating in the national Diabetes Detection Initiative DDI of
the US Department of Health and Human Services The primary focus of
this initiative is to help people understand their diabetes risk by knowing
the risk factors and assist high-risk people in linking with various health
care systems and health care professionals to discuss testing

California has evaluated the success of its efforts through
multiple
methods that identify short-term, long- term and process outcomes The
State is following CDCs logic modeling, looking at data to inform and help
guide future efforts They are using measures that are already being
collected and then deriving ways to fill in the gaps In addition to
quantitative data, California is collecting qualitative information through
focus groups and surveys of partners about the effectiveness of
communications and messages

Michigan

As part of its DPCP, the State of Michigan has set up a statewide network
aimed at ensuring comprehensive diabetes management

The program, established as part of the Michigan Department of Community
Health, Division of Chronic Disease and Injury Control, gained more
resources in 1994 after receiving a CDC comprehensive grant and funds from
the new State tobacco tax revenues The States Upper Peninsula region
staff developed a model for working with health care providers on providing
quality care and professional education aimed at improving diabetes care in
the Finnish population When the data showed that people served in the
region had better outcomes, DPCP established six regional Diabetes Outreach
Networks DONs
statewide Michigans DON Diabetes Care Improvement
Project was recognized as a Best Practice Initiative in 2002 by the
Assistant Secretary for Health at the US Department of Health and Human
Services

Each DON in Michigan develops collaborative partnerships with health care
delivery agencies, sponsoring and providing professional education, and
coordinating and developing diabetes resources within their service region
Such collaboration of diabetes care resources is aimed at increasing
awareness and ensuring that persons with diabetes and at risk for diabetes
are identified and receive ongoing diabetes care and education While the
regional networks have some efforts that are unique to their area, much
work is done on a statewide basis The entire staff meets three times a
year and holds conference calls on a monthly basis to coordinate efforts
and develop programs

Results from the Michigan DON demonstrate that working with health care
agencies and providers through a statewide Diabetes Care Improvement
Project can result in improved outcomes for persons with diabetes Trends
in follow-up data from fiscal year 1996-2001 show a significant increase in
the number of persons with
diabetes receiving important tests
Individualized data analysis from the regional DONs also shows a positive
downward trend in the levels of HbA1c, which is associated with
significantly reduced risk of complications The program has demonstrated
local reductions in diabetes-related hospitalizations, amputations, and
mortality The program began seeing these results relatively soon after
implementation and has begun to close the gap between Michigans diabetes
averages and the national average

Michigans Diabetes Policy Advisory Council works with DON directors and
provides an opportunity for sharing information, best practices, and
networking In an effort to increase awareness and gain more support,
regional directors meet regularly with area legislators to share
information, identify gaps, and discuss how the legislature can help reduce
the burden of diabetes In addition, they meet with citizens and inform
them about how they can seek legislative support

Involvement by elected officials in diabetes related events has created
momentum for the effort Michigan was one of a group of States that
participated in the Chronic Disease Academy sponsored by the CDC and hosted
by the
National Governors Association A team of agency directors,
legislators, and advocacy groups attended this 3-day session and created a
strategic plan for addressing chronic disease issues in the State One of
the ideas the State has implemented is a prevention caucus for legislators
Recently the group launched a challenge among State officials to adopt
healthier habits People in all branches of State government are now
clocking their steps when they exercise and competing to be the most
active Even the Governor is wearing a pedometer Involvement by elected
leaders has attracted press attention and is raising public awareness

The appointment of the States first Surgeon General, Dr Kimberlydawn
Wisdom, has served to identify synergies between various efforts In
October 2003, Michigan presented its new Michigan Diabetes Strategic Plan
Developed by the Michigan Department of Community Health, the Michigan
Diabetes Prevention and Control Program, and the Michigan Diabetes
Strategic Plan Task Force and its Steering Committee, the plan addresses
issues related to diabetes care and prevention It also establishes a
unified course of action among health care providers, public and
private
health officials, researchers, businesses, community groups, and people
with diabetes to implement the most promising diabetes prevention and
control strategies in the most cost-effective ways Some highlights of the
report include:

Expanding diabetes primary prevention activities

Developing an ongoing public awareness campaign

Developing a Statewide diabetes consumer advisory group

Reducing diabetes-related health disparities among minority populations

Providing quality diabetes pregnancy-related care and education to women
Dr Wisdom and US Surgeon General Dr Richard Carmona recently announced
the involvement of Flint, Michigan in the DDI In Michigan, the DDI will
concentrate on the undiagnosed populations with a paper risk assessment
test that can be followed up by a blood test and further treatment as
necessary Materials for the paper assessment are available through a
variety of community channels such as social services, faith-based
establishments, retail outlets, and fraternal organizations
Missouri

The States DPCP has identified diabetes as a serious public health problem
Missouri Department of Health and Senior Services, 2002 Citing studies
showing
that interventions can prevent or delay diabetes complications, the
States DPCP has led the effort to implement the Chronic Care Model

The department has collaborated with federally qualified health centers
FQHCs and one National Health Service Corp site in HRSAs Health
Disparities Collaborative for diabetes Participating clinics were chosen
strategically in an effort to align disease impact with a service provider
who was ready and willing to work on the project Each center implemented
the Chronic Care Model in one or more clinics, forming teams of diabetes-
related health care specialists Each center established an initial
registry of patients with diabetes Additional provider and/or site
registries were added as the year progressed The electronic registries
were used to monitor indicators of health behavior, health status, and
services received Monthly summary registry reports were sent to the
States DPCP, where the data were aggregated The States DPCP provided
FQHCs with financial support, a local learning session, technical
assistance on registry development, maintenance, health system redesign,
monthly reports, and evaluation skills

From June 2000 to May 2003,
preliminary results indicated health centers
significantly improved 12 of 16 diabetes-related care measures, including
increases in the prevalence of at least two HbA1c tests at least 3 months
apart an increase of 15 percent, dilated eye exams 190 percent, foot
exams 47 percent, influenza vaccinations 76 percent, and whether the
patient set self-management goals 37 percent Future efforts will focus
on maintaining these improvements and extending Collaborative activities to
other health care sites

The DPCP has tapped other resources by working closely with the States
cardiovascular disease program and MissouriPRO, which has a contract from
CMS to manage quality improvement on behalf of beneficiaries MissouriPRO
helped lead the training and implementation process for expanding the
Collaborative to include 10 additional health providers DPCP sees this
partnership as a strategic alignment, expecting changes by CMS providers
ultimately to have an impact on the rest of the State

North Carolina

North Carolinas DPCP initiated a number of diabetes initiatives including
a unique community-based program, Project DIRECT, that targets diabetes
prevention and care efforts in the
African-American community Using a
comprehensive approach, Project DIRECT Diabetes Interventions Reaching and
Educating Communities Together encouraged exercise and improved nutrition,
promoted awareness of diabetes, and increased screening for diabetes CDC,
2003e

Early on, the DPCP pulled together a statewide diabetes advisory council
that included all stakeholders The group became active in advocacy and
policy issues Their support was crucial in helping secure matching funds
from the State legislature that allowed them to gain more resources from
CDC as a basic implementation program In 1996, members of the council
successfully pushed legislation mandating that insurance cover diabetes
education and testing strips The most recent legislative action was the
2002 Care for School Children with Diabetes Act At the time of passage in
2002 only three States had this kind of legislation for children in the
public school system The law ensures that the needs of students are
addressed through an individualized diabetes care plan that includes
provisions for snacks, testing, and assistance from an adult The advisory
council was very active in getting the bill passed

North Carolina
has reached 91 percent of its diabetes goals in the last 4
years, seeing increases in foot exams, eye exams, flu shots and HbA1c
tests The State has also met its goals in improvement among minority
groups The DPCP has begun working with the State QIO to examine Medicaid
reimbursement claims for diabetes care, especially information on children

Selected Local Quality Improvement Efforts

In addition to national, Federal, and State quality improvement approaches,
there are also local efforts to improve diabetes care quality Local
quality improvement initiatives are a crucial part of overall efforts
because they are closer to and have more direct contact with providers and
local health systems Quality improvement programs and models, such as the
Breakthrough Collaboratives or the Plan-Do-Study-Act model discussed
further in Module 5: Improvement, are best implemented at the local level
Yet, State-level support is critical to local efforts because payment
structures, as well as the legal and regulatory structure of the health
care market, are largely a State responsibility

There are any number of local quality improvement initiatives that exist
for diabetes, too many to list
here In addition to the Health Disparities
Collaboratives which involve the Federal, State, and local levels, two
additional examples of local diabetes projects are included as
illustrations of the links between national, Federal, State, and local
contexts:

The St Louis Diabetes Coalition is a voluntary network of health plans,
provider groups, and other community organizations and companies that are
working together to improve diabetes awareness, education and adherence
to standards of care in the St Louis area The Coalition has worked
together on a number of initiatives, including its Diabetes Screening and
Treatment Guidelines The treatment guidelines were endorsed by all of
the major health plans in the St Louis region, giving providers a single
source for diabetes guidelines acceptable to all major payers The
Missouri Department of Health and Senior Services worked alongside the
Coalition members to distribute the guidelines to more than 5,000
physicians in St Louis and other parts of Missouri More information
about this and other the St Louis Diabetes Coalition initiatives is
available at http://wwwdiabetescoalitionorg

The Niagara
Health Quality Coalition NHQC is a local organization of
employers, providers, physicians and insurers in western New York
dedicated to working together to achieve quality, affordable health care
NHQC is affiliated with the Buffalo Niagara Partnership, the largest
employer organization in the Niagara area representing 3,300 firms with
more than 200,000 employees Stating that data are national but change is
local, the NHQC provides links to both State and national data that can
help local organizations, companies, and individuals become informed
about the quality performance of various health care sectors The NHQCs
Web site, http://wwwmyhealthfindercom, links to hospital, health plan,
physician, and long term-care quality data The site also has links to
clinical care guidelines for diabetes that were developed by the State
diabetes coalition

Summary and Synthesis

The breadth of diabetes quality improvement activities both nationally and
across the States provides State leaders with a variety of proven
experiences, useful resources, lessons learned, and best practices for
enhancing initiatives and partnerships in their own States State
programs
have been successful in making inroads in diabetes prevention and quality
improvement
Yet, there is still much that can be done Despite the efforts of States,
national organizations, the Federal Government and a host of local and
community efforts, there is still room for improvement Diabetes rates
continue to rise, substantial gaps in care for diabetes exist, preventable
complications occur all too frequently, and the Nation is paying the price
in higher health care costs and lower productivity and quality of life

State leaders may also wonder which quality improvement strategies are the
most promising approaches to achieving real improvements in diabetes care
quality While this question cannot be answered conclusively for the
public policy arena, a recent research analysis of diabetes quality
improvement strategies in clinical settings provides some evidence for
prioritizing certain approaches A systematic review of the literature on
clinical diabetes quality improvement strategies found that provider
education ie, meetings or conferences, outreach visits, and distribution
of educational materials and disease management were the most effective
strategies in achieving
significant improvements in patient HbA1c levels
However, the study also found multiple quality improvement interventions
achieved more significant improvements in HbA1c levels and provider
adherence to clinical guidelines than single interventions Shojania,
McDonald, Wachter, et al, 2004

Before embarking on any particular public policy approach, however, State
leaders will need to assess what is already being done to address diabetes
care quality in their State Talking with DPCP officials in the State
health department, Medicaid directors, State employee benefit officials,
State and community stakeholder group leaders, provider associations and
professional societies can help State leaders assess what is already
underway in the State, which efforts have been most successful and where
additional efforts are needed The State Diabetes Quality Improvement QI
Inventory, presented in Table 42, is designed to assist State leaders in
assessing the range of diabetes programming and determining the appropriate
stage of development of an activity

Based on this inventory, State leaders are ready to move to the next stage
in the quality improvement process - actually developing a
quality
improvement strategy for a State The next module of the Resource Guide is
designed to assist State leaders with planning and implementing diabetes
quality improvement action strategies by using information from previous
modules in applying the PDSA model of quality improvement to the public
policy setting Module 5: Improvement also discusses important components
of evaluation plans for State efforts

Associated Appendixes for Use With This Module

Appendix G: Index of Diabetes Quality Improvement Initiatives
Appendix G provides brief descriptions and links to further information for
a variety of national and federal diabetes quality improvement initiatives
State leaders may want to review and consider these programs as models or
resources for State action

Appendix H: CDC and State Funding for DPCP, by State, 2003-2004

Appendix H shows the funding provided by the CDC to each State for the DPCP
and each States contribution State contributions are shown by general
funds and in-kind resources

Module 5: Improvement - Developing a Strategy for Diabetes Quality
Improvement

As rates of diabetes increase across the country, roughly tracking with
increases in obesity rates, States are quickly approaching a time when
budgets will not be able to withstand the pressure of treating the flood
of obesity-related diseases Consequently, while we search for better

and more efficient ways of treating diabetes and helping people manage
the disease so that costly procedures can be prevented, we must find more
ways to create incentives for people to make healthy lifestyle choices
The State that figures out how to do this, while respecting and
protecting individual liberties, will be the model for the Nation

- An Interview with Governor Mike Huckabee, Arkansas

Quality health care is a goal that all health care professionals and
policymakers can achieve, yet many do not know where to begin

The challenge of the health care system is to define what is quality
health care and lead participants in the health care system to increase
quality, reduce mistakes, and attain quality results for every patient
every time Some may view this as impossible Others can point to the
great strides that have been made in manufacturing and other services by
applying the principles of quality improvement And some can point to
dramatic improvements in reducing deaths in US hospitals from applying
the principles of quality improvement Gabor, 2004 Additionally, a
number of States today can point to gains that they have made in
diabetes
outcomes for their citizens to confirm that quality improvement in health
care is possible

Module 1: Background provided an overview of diabetes and quality
improvement Module 2: Data provided a variety of data sources with State-
specific data on diabetes quality of care Module 3: Information helped
State leaders understand how data must be examined to make comparisons and
create information for guiding decisions and leading change Module 4:
Action offered a variety of national, Federal, State, and local approaches,
resources, and best practices that can inform State quality improvement
efforts

This module aims to assist State leaders to develop diabetes quality
improvement strategies suited to State contexts Module 5: Improvement
provides models for quality improvement, presents a case study of how one
State - Wisconsin - undertook an ambitious quality improvement effort, and
discusses how State leaders can begin to develop their own State-specific
strategies to improve diabetes care quality

A Model for Quality Improvement

While local contexts differ, models of quality improvement give the common
elements needed to stimulate change and improvement in any
situation As
State leaders embark on new initiatives or revitalize existing ones,
quality improvement models can inform those efforts The key is to find a
suitable model for an individual State and its partners, and then pick and
choose the components that are most useful for a specific local context
Explained below is a model that may be useful for State leaders developing
quality improvement strategies

Plan-Do-Study-Act PDSA Model

A time-tested quality improvement tool still useful today is the Plan-Do-
Check-Act or the Plan-Do-Study-Act model for guiding quality enhancement
projects of all types see Figure 52 The PDSA model conceptualizes the
continuing cycle of improvement

Its steps for effective quality improvement include:

Plan - Set the goals of the quality improvement cycle-questions,
predictions, data to be collected, and the who, what, when, where of the
project

Do - Carry out the plan and document problems and unexpected
observations

Study - Complete the analysis of the data, compare to predictions, and
summarize lessons

Act - Determine changes to be made and decide what will happen in the
next cycle Langley, Nolan, Nolan, et al, 1996

Figure 51

Source: Adapted from Langley G, Nolan K, Nolan T, et al The
Improvement Guide: A Practical Approach to Enhancing
Organizational Performance San Francisco: Jossey-Bass
Publishers, 1996

The PDSA cycle usually applies at the point of production, in this case to
the front-line of health care at the point of care The concept also can
be applied to the quality improvement role of State leaders Drawing on
insights from State quality improvement activities around diabetes care,
State leaders might consider a Partner-Plan-Do-Study-Act model

Partner - Decide who are strategic partners of quality improvement and
recruit them to the project - champions in health care production,
stakeholders eg, consumer/patient groups, health care professionals,
purchasers, health plans, and topic experts, among others, and key State
leaders and agencies eg, visible champions, diabetes experts, program
planning/evaluation staff and quality improvement experts Is the group
large enough to include key leaders and perspectives, yet small enough to
be productive?

Plan
- The goals of a project will be broad in the context of statewide
activities because many partners and processes will need to be involved
What does the group predict are the current obstacles to quality care?
How will the goals be put into action? What data need to be collected to
prove that the changes are indeed improvements?

Do - Test the plan and document problems and unexpected observations as
data are collected Initial plans seldom produce desired results the
first time Pilot test the ideas of the group with front-line health care
programs, providers, and consumers Reconvene the partners and discuss
successes and problems

Study - Complete the data analysis, compare the results to predictions,
and summarize lessons learned Do the test results convince the partners
that full-scale implementation will be successful? Because the scope of
activities may be broad and costs may be involved, the planned action
should be based on reasonable data and results

Act - Determine the changes to be made Implement the changes State- or
district-wide Continually assess those changes through data collection
and analysis Are the changes
working? What will happen in the next
cycle?

The PDSA is one model of quality improvement that has withstood the test of
time There are other tools and methodologies for quality improvement to
suit the various stages at which States find themselves Following are
additional resources that States might want to use to facilitate quality
improvement wherever they are along the continuum

The Quality Assurance Project, sponsored by the United States Agency
for International Development USAID, presents models based on
quality improvement on an international scale These models are
useful and easily translated for States information available at
http://wwwqaprojectorg/resourcesintrohtml

The IHI breakthrough series focuses on change at the provider level,
but is an important approach that State leaders should understand for
developing change agents information available at
http://wwwihiorg/ihi

Numerous tools are also available to further assist quality improvement
projects Quality improvement tools suited for policymakers are available
on AHRQs Quality Tools Web site
at:
http://wwwqualitytoolsahrqgov/channels/channelaspx?mode3incbrowsepol
icy_makersinc For another quality toolbox, see Tague 1995

The PDSA model can be applied to the context of State leadership in quality
improvement The actual approaches and actions that States will take will
be as varied as the examples that appear in Module 4: Action of this
Resource Guide One States experience, in particular, can help illustrate
how the PDSA model can be applied to an actual quality improvement project

PDSA Case Study: Wisconsin Collaborative Diabetes Quality Improvement
Project
Wisconsins DPCP, part of the Wisconsin Department of Health and Family
Services, received CDC funding in 1994 and other funding since then Over
time the DPCP developed an ambitious strategy to improve diabetes care
quality for clients of managed care organizations Wisconsins diabetes
quality improvement efforts in many ways mirror the stages of the PDSA
model described above

Partner - In 1996, the DPCP formed the Diabetes Advisory Group comprised
of over 50 diverse groups and organizations Wisconsins health
maintenance organizations HMOs were key partners in the advisory group

Plan - One of the
first plans developed by the Diabetes Advisory Group
was the development of Diabetes Mellitus Care Guidelines and supporting
documents for use by all health care providers in the State Released in
1998, these guidelines were endorsed by the Advisory board members, and
members promoted the use of the guidelines throughout the health care
system blanketing the State with a common message about quality diabetes
care The DPCP used materials from other States and also worked with the
University of Wisconsin-Madison to use data to assess the status of
diabetes care in the State and adherence to the Diabetes Mellitus Care
Guidelines

Do - Out of this successful effort, the Wisconsin Collaborative Diabetes
Quality Improvement Project was established in 1999 The goal of the
Diabetes Quality Improvement Project is to improve the quality of
diabetes care for people who receive services through Wisconsins HMOs
and two other large health systems by:
o Evaluating implementation of the Wisconsin Essential Diabetes Mellitus
Care Guidelines
o Sharing data issues, strategies, initiatives and lessons learned
o Improving diabetes care
through collaborative quality improvement
initiatives

Collaborators included university experts, Wisconsins QIO, the State
Medicaid program, and other health care industry partners The department
used a two-pronged approach to convince the HMOs to sign on First, they
leveraged the support of a well-connected spokesperson to discuss the
guidelines and the possibility of forming the collaborative Secondly,
they participated in ongoing discussions about quality improvement in the
private sector They presented the collaboration as a potential win-win
opportunity HMOs would get value from the project through access to
information, tools and ongoing support as well as receiving good media
coverage for their work with the State The DPCP would reach the 68
percent of the States population served by the participating HMOs

Study - Collaborators used the Health Plan Employer Data and Information
Set HEDIS comprehensive diabetes care measures to track progress in
improving diabetes care The States DPCP contracted with the University
of Wisconsin to provide confidential analysis and reporting Each HMO
was given a confidential
identifying number so it could see how its
performance compared with other organizations The project was careful
to use these data results cooperatively, not competitively, with a goal
of improving diabetes care in Wisconsin Participants in the
Collaborative continued to discuss issues and strategies such as registry
development, data collection, and provider profiles

The quality improvement plan included evaluative efforts to assess
improvements in diabetes care An evaluation of the HEDIS data showed
that the project:
o Increased eye exams for people with diabetes from 62 to 69 percent

o Increased cholesterol screening and control from 72 to 78 percent
and 45 to 51 percent, respectively
o Increased kidney disease monitoring from 47 to 52 percent

Act - With data collection and reporting in place, the Wisconsin
Collaborative Diabetes Quality Improvement Project took further action by
focusing its quality improvement efforts With HbA1c rates already at 90
percent in the State but eye examination rates much lower, the partners
determined that the project should establish a statewide Diabetes Eye
Care
Initiative In 2001, this project began with the goal of increasing
eye examination rates and enhancing communication among specialists and
primary care providers related to diabetes eye care

In October 2003, the project released a compendium of the diabetes
quality initiatives implemented in the 5years since the project began
In addition to describing the interventions used, the compendium provided
information on barriers, ongoing challenges, and lessons learned Some
of the lessons and strategies used to achieve the encouraging results of
the project were:
o More inclusive quality improvement teams over time
o Increased use of diabetes care teams, champions, and case management
services
o More in-depth barrier analysis and intervention evaluation
o Community collaboration
o More advanced information systems for developing, tracking, and
feedback on targeted interventions
o Support for providers and clinics
o An increased focus on the role of the consumer
o Increased use of technology to enhance communication and outreach
Wisconsin Department of Health and Family Services, 2003

More information on the
Wisconsin Collaborative Diabetes Quality
Improvement Project, is available at:
http://wwwdhfsstatewius/Health/diabetes/Diabetes_Collaborative_Improveme
nt_Projecthtm

As this case study demonstrates, quality improvement can take many years
and iterations before actual change and quality improvement can be
documented However, the reward is that once the partnerships and
processes are in place there is the opportunity to see measurable advances
in care quality and in health outcomes

Developing a State Strategy for Improving Diabetes Care Quality

The PDSA quality improvement model described above can be combined with
previous modules of this Resource Guide to build a strategy for improving
diabetes care quality AHRQ has also developed a companion Workbook that
can assist State leaders through a step-by-step process for using the data,
information and resources from this Resource Guide to develop the case for
diabetes quality improvement in a particular State, examine strategic areas
for improvement, and develop a detailed strategy

Described below are tools that can help State leaders develop a State
quality improvement strategy These tools can be used in conjunction with
the
Workbook exercises The first tool is the State Diabetes Quality
Improvement Worksheet see Figure 52 that can assist State leaders with
assembling the data about their State and diabetes Another tool is the
PDSA checklist that provides the common steps State leaders need to take to
build a quality improvement strategy In working through these tools,
State leaders are advised to work closely with State DPCP officials to plan
and develop their States diabetes quality improvement strategy

Building the Case for Diabetes Quality Improvement

One step in the process of developing a quality improvement strategy is for
State leaders to gather information about diabetes in their State The
worksheet below helps State leaders to assemble State-specific information
on diabetes prevalence, cost and quality of care to assess opportunities
for improvement This worksheet information combined with the inventory of
programmatic activities related to diabetes assembled at the end of Module
4: Action allows State leaders to assess the current condition of diabetes
care and public policy in their State Using this information, they can
make the case that diabetes quality improvement is important for
their
State

Figure 52 State Diabetes Quality Improvement Worksheet

From Table 23 - State-Specific Estimate of Cost Burden of Diabetes:
Number of people with diabetes

Percent of the population with diabetes

Direct cost of diabetes in the State

Indirect cost of diabetes in the State

From Table 21 - NHQR Diabetes Quality Measures
HbA1c testing rate two or more times per year in the State

national average 61
HP 2010 goal 50
Best in class State average 82
Retinal eye examination rate in the State
national average 67
HP 2010 goal 75
Best in class State average 81
Foot examination rate in the State
national average 65
HP 2010 goal 75
Best in class State average 82
Flu vaccination rate in the State
national average 37
HP 2010 goal n/a
Best in class State average 58

From Appendix H - CDC and State Funding for Diabetes Program
CDC funding
State in-kind and general funding
State funding in States with similar disease burden

State funding ranges in surrounding States

From Appendix F -
NHQR Quality Measures for Various Conditions
Measures on which state is below average indicated by a minus sign in the
column for the state

Putting the PDSA Model To Work

The adapted PDSA model is a general model intended to capture the most
important components of quality improvement; but State leaders may wonder
how to put it to use Provided below is a checklist of PDSA quality
improvement steps This checklist outlines the common steps that State
leaders need to take to develop a quality improvement strategy Using the
checklist as a framework, State leaders can fill in the State and local
background, data, information, public policy approaches and other resources
to develop a strategy suited to their particular context

As State leaders do this, one of the most important factors to bear in mind
is the cyclical nature of quality improvement Improving health care
quality is not a one-time activity but must be ongoing Sustained
improvement usually occurs over many years Thus, the most effective
action plans will include not only short-term goals but long-range ones as
well

Integrating Quality Improvement Activities Across Conditions

Diabetes is one of several
chronic illnesses with demonstrated
opportunities for quality of care improvements Care for asthma, cancer,
heart disease, and other common chronic conditions affecting millions of
Americans too often falls short of what research has indicated to be the
most effective treatments Diabetes and other chronic conditions combined
account for 78 percent of all health care spending and 7 out of 10 deaths

State leaders can use this information to help decide how broadly or
narrowly to focus their quality improvement efforts Diabetes may be just
one of several costly health care conditions that are appropriate areas to
invest in quality improvement efforts in a given State In addition, there
may be advantages to integrating quality improvement efforts across several
conditions, such as stretching scarce resources by using economies of scale
across programs, minimizing investment costs in infrastructure, and
maximizing the effect of systemic changes in health care delivery

Thus, some States may choose to expand on existing diabetes quality
improvement efforts while other States may want to establish comprehensive
quality improvement efforts that target several diseases at once
For
example, several States, including Wisconsin, have expanded their efforts
with diabetes to address heart disease since the two are related On the
other hand, Vermont has initiated a broader chronic care initiative to
improve the quality of care for all chronic diseases but has chosen
diabetes as the first focus area for the initiative See the Vermont
Chronic Care Initiative Web site at
http://wwwhealthyvermontersinfo/hi/chronic/chroniccareshtml for more
information

The Importance of Evaluation

Evaluation is essential to understand whether a quality improvement
activity is accomplishing planned goals, whether goals and actions are
ultimately improving the health outcomes of the population, and what
adjustments are necessary Evaluation in quality improvement can be done
quickly, as often suggested by facilitators, to maintain momentum of the
quality improvement activity Evaluation can also look at longer term,
underlying components of the program One program that can serve as a
resource for State leaders in developing an evaluation plan for diabetes
quality improvement efforts is the CDCs accountability efforts for State
DPCPs

In 1999, the CDC began addressing the
need for more systematic State-level
programmatic evaluation and accountability in the National Diabetes
Prevention and Control Program The CDC devised seven national objectives
for diabetes care, including increasing the percentages of people with
diabetes receiving HbA1c testing, eye exam, foot exam, and influenza
vaccination In addition, the national objectives include reducing health
disparities and establishing linkages to other wellness programs, such as:
physical activity or smoking cessation programs for people with diabetes

The CDC asked States to devise their own State objectives for improved
diabetes population health in order to address the uniqueness of each
States population A critical objective that States usually include is to
establish measurement procedures to track progress The CDC focus on
evaluation emphasizes the importance of measurement The State DPCP has
become a catalyst for statewide improvements through partnering and
accountability on various operational levels

CDC Model for Program Evaluation

The CDC employs a model of evaluation that includes four groupings of
standards for program evaluation, and six repeating steps in the evaluation
process
as illustrated in Figure 53

Figure 53 CDC model of evaluation

Source: Centers for Disease Control and Prevention Framework
for Program Evaluation in Public Health MMWR 1999;48No RR-
11 Available at: http://wwwcdcgov/eval/frameworkhtm
accessed March 3, 2004

The CDC provides 30 standards under the four subgroups of utility,
feasibility, propriety, and accuracy These standards are guidelines for
conducting sound and fair evaluations and may be briefly described as
follows:
Utility ensures that the evaluation serves the needs of intended users
Feasibility results in evaluations that are realistic and sensible
Propriety ensures ethical integrity in the conduct of the evaluation
Accuracy leads to information that is technically sound

Steps in the Evaluation Process

The six steps in the evaluation process may vary as to when they are
carried out, though one step usually lays a foundation for the next Steps
will be repeated as results become clear and new issues arise Each step
serves to ensure the effectiveness of the evaluation

Engaging stakeholders is
essential to ensure that the evaluation
addresses the important elements of the program and that the evaluation
is used Stakeholders include those served by the program, those planning
and directing the program, and those involved in program operations

Describing the program serves two functions First, it lays out in
detail the programs goals and strategies so that everyone involved
understands them Second, it provides an opportunity for consensus
building around the goals and strategies

Focusing the evaluation design addresses the greatest issues of concern
This step includes identifying the purpose of the evaluation; defining
the users and usefulness of the evaluation; listing stakeholders
questions that need to be addressed; establishing methods to ascertain
information upon which the evaluation will be based; and developing
consensus around particular roles and responsibilities pertaining to the
evaluation

Gathering credible evidence contributes to the robustness of the
evaluation Developing credible evidence involves defining appropriate
indicators, identifying legitimate sources of information; ensuring the
quality of
data gathered; and aligning the infrastructure for collecting
evidence with the environment and individuals from which the
information is gathered

Justifying conclusions is important to ensure that the evaluation will be
used When consensus is reached regarding the goals and strategies of
the program, when the values of the evaluation are aligned, and when the
evidence gathered is credible, then conclusions will naturally be
justified At this point, conclusions and recommendation can be made

Ensuring use and sharing lessons learned includes designing mechanisms
for feedback and dissemination of the information gained in the
evaluation

Employing an evaluation specialists or, at the least, assembling an
evaluation team with a designated leader will help facilitate the process
Issues regarding internal bias and external influences must be addressed to
ensure integrity of the analytic work and a trusted evaluation of a program
or project

To be effective, however, evaluation strategies must be timely and useful
They should be considered at the beginning of the project and they should
have a reasonable deadline for completion Including an
experienced
evaluator on the quality improvement team can help ensure that the
evaluation will be sound, useful, and timely The evaluation should feed
back to the quality improvement cycle and direct future actions

Summary and Synthesis

Module 5 has provided a model of quality improvement, a case study of one
States innovative quality improvement strategy and some tools and
considerations to help State leaders develop their own quality improvement
strategy This module does not provide States with one approach or answer
Instead, decisions about the kind of quality improvement strategies that a
State should pursue are the responsibility of State leaders and their
partners, who are positioned to know what is best suited for their State
context

There are common elements to quality improvement that can inform the
development of State strategies The PDSA model adapted for the
policymaking context is one approach that can assist State leaders It is
also important that State innovators examine the current condition of
diabetes care and what diabetes programs are underway State quality
improvement efforts can then build on and fill in the gaps to develop a
more comprehensive,
coordinated approach to improving care Because
quality improvement occurs over a long time frame, evaluation is crucial to
determine what effects the strategy has had and to justify continued
efforts and resources over time

Resources for Further Reading

Langley G, Nolan K, Nolan T, Norman C, Provost L The Improvement Guide: A
Practical Approach to Enhancing Organizational Performance San
Francisco: Jossey-Bass Publishers, 1996

Tague NR The Quality Toolbox Milwaukee, WI: ASQC Quality Press, 1995

Associated Appendix for Use With This Module

Appendix F: NHQR Quality Measures for All Conditions by State

Appendix F provides quality measures for all conditions and topics in the
NHQR It includes the national estimate and an indicator for whether or
not the State estimate not shown due to space limitation is statistically
greater, lower, or no different from the national average This resource
can help States identify which diseases and their treatments may be in need
of attention

Module 6: The Way Forward - Promoting Quality Improvement in the States

Quality health care means doing the right thing at the right time in
the right way for the right
person and having the best results
possible AHRQ, 2003c

Health care analysts and researchers have long documented extensive gaps in
the quality of care delivered to Americans Despite unrivaled
technological innovation in American health care, too much of the care that
is delivered to patients does not meet the accepted standards of quality
The findings of the National Healthcare Quality Report and the National
Healthcare Disparities Report provided further confirmation that, while in
some areas care is improving, the health care system in America has a long
way to go before it delivers care that is consistent with accepted
guidelines and does not vary significantly by geography, race, ethnicity,
or socioeconomic status

There is a great deal that State leaders can do to support and encourage
quality improvement, and thereby, to improve health outcomes, reduce the
burden of disease, and possibly increase the efficiency of the health care
system As guardians of public health and health care innovators, States
can champion quality improvement and best practices that can transform
health care systems In most cases, State government is also one of the
largest health care
purchasers in a State due to Medicaid and State
employee health insurance programs With States experiencing budget
problems and high growth in health care costs, States cannot afford to pay
for a product that does not meet accepted standards of quality Alone or
in concert with other purchasers, State governments can help steer the
health care system toward the consistent delivery of high quality care

Diabetes is one chronic condition that has a compelling case for quality
improvement for States The disease burden from diabetes is great in terms
of the number of people affected, the cost of complications, its effect on
quality of life, and the disparities in care between racial and ethnic
groups Despite its prevalence and cost, research has demonstrated that
type 2 diabetes can be prevented, and complications from both type 1 and
type 2 diabetes can be prevented or significantly delayed with appropriate
treatment Diabetes also has widely accepted, evidence-based guidelines
for care and a strong case for a return on investment for purchasers and
society from diabetes quality improvement efforts

The NHQR provides an array of national and State-level data that can help
States
focus their quality improvement efforts This Resource Guide has
taken the data from the NHQR on diabetes and placed it within a model of
quality improvement to assist States with improving diabetes care State
leaders now have the opportunity to contribute to the growing momentum to
improve the quality of care in America through State initiatives

What Can State Leaders Contribute to Quality Improvement?

As State leaders examine how they can be involved in improving the health
care quality, there are a number of essential elements that State leaders
can contribute to the process These elements include: providing
leadership and shared vision, fostering partnerships and collaborations
between key parties, planning and setting goals, enhancing measurement and
reporting, improving the infrastructure of health care quality, assuring
evaluation and accountability, and creating incentives

Providing leadership and vision-Quality improvement requires leadership
It will not emerge without a champion who can provide leadership for
organizations and individuals to work together to develop a shared vision
and common goals for health care quality Whether initiatives are

developing locally, statewide or nationally, effective leadership is
essential to quality improvement However, health care quality cannot be
accomplished by one champion, be it a person or an organization
Leadership must be a catalyst for others to become involved in developing
shared vision and goals for improving health care quality

Forming partnerships and collaborations-In addition to leadership and
vision, partnerships and collaborations are vital to improving quality
Health care quality is the product of many different parts of the health
care system but ultimately must affect what happens in the community, the
patient environment, and the clinical setting Thus, all of the groups
that have an effect on patient care should participate in quality
improvement efforts for an initiative to be successful, including health
care professionals, providers, patients, and purchasers Health care
professionals and providers need to establish systems that deliver
appropriate, quality care consistently; patients need to demand and
participate in the best available care; and purchasers must demand and
pay for the highest quality, most
cost-effective delivery of care
Consumer groups with interest in diabetes can be powerful allies for
change and a source of expertise State health department staff and
other diabetes care experts from private sector organizations can provide
support and expertise for State initiatives

Assisting planning and goal setting-Once partnerships and collaborations
are initiated, the quality improvement group must develop an action plan
with specific goals for quality improvement in the State The action
plan must include timelines for specific steps and deliverables to help
ensure that all partners move together The plan should include specific
responsibilities and benefits for as many project partners as possible to
ensure buy-in and continued involvement

Enhancing measurement and reporting-Another essential piece for
understanding quality is defining quality standards and developing
measures to track how well or poorly the quality improvement intervention
is working and the health care system is performing In addition to
assessing quality-improvement activities, measurement and reporting
provide a mechanism for comparing how well any
given health plan or
provider is doing in a selected area of care Quality measurement can
involve counting the number of patients who received a needed
immunization or screening or how often patients had to be hospitalized
due to complications after a surgery by a given provider Health care
providers and companies must have data systems that are robust enough to
estimate a given set of measures of health care quality Results then
must be made available for purchasers and consumers to be able to make
meaningful comparisons of the performance of various providers As
discussed earlier in the Resource Guide, there is a well developed set of
measures for diabetes care quality and many existing data collection and
reporting systems that are available to States There is a wide array of
public measures and publicly available data sources reported in the NHQR,
as well as other important measures that States may want to incorporate
into a quality improvement and evaluation strategy

Improving the health care infrastructure-Part of quality improvement is
the ability to make necessary adjustments in the infrastructure of health
care
Infrastructure in health care can include professional education,
data systems, financing and delivery systems, research, and patient
education resources, among others Health care quality evaluation by its
nature highlights areas for improvement, thus drawing attention to areas
where health care professionals may need additional education or
training, where providers may need to redesign systems of care, where
payers need to improve financial incentives, and where purchasers need to
allocate more resources to address quality concerns and reward superior
performance Evaluation of health care quality can also reveal areas for
further research and ways that patients can be actively engaged in
managing their care and changing behavior such as smoking cessation,
nutritional improvements, or other areas that may contribute to health
care problems

Assuring evaluation and accountability-After establishing partnerships
with solid leadership and common vision and goals, measuring and
collecting data on quality, and reporting it for comparison, there also
is the need for evaluation of both health system performance and
accountability for
health care quality Evaluation allows partners to
identify the most troublesome areas and prioritize resources and
attention to those areas that most need improvement Evaluation promotes
the opportunity to celebrate areas where there is solid performance or
conduct improvement over time It may require some technical input and
expertise, but it is an important component of the quality improvement
process Without evaluation, impact of the program will be unknown and
future direction for the program will be haphazard

Creating incentives-While reporting data on performance is often enough
to spur low performers toward improvement, there is also the need to tie
rewards to high performance Currently, the American health care system
essentially pays all providers the same regardless of the level of
quality that they deliver Without adequate rewards for improvement,
health care quality will languish As one of the largest health care
purchasers in any given State, State governments can have a tremendous
influence over incentives for quality improvement in the health care
system through their payment structures

This Resource Guide has
attempted to demonstrate for State leaders the need
for quality improvement in diabetes Much has been done, but data from the
NHQR show that much remains to be done to achieve quality diabetes care for
all people with diabetes The number of people newly diagnosed with
diabetes and the number suffering its complications are still growing

By reviewing and analyzing this Resource Guide, assessing their local
context, and designing a diabetes quality improvement strategy, State
leaders can identify opportunities to make a difference in the quality of
care their constituents receive The experiences of States that have
implemented quality improvement for diabetes care provide valuable insights
into what can be accomplished through innovative, visionary efforts by
State leaders

References

Agency for Health Care Administration AHRQ, 2000 The Florida Medicaid
Disease Management Initiative: A report on the Florida Medicaid
Disease Management Program - Historical perspective, start-up
activities, current operations, future operations and expectations
Available at: http://wwwstatecoveragenet/statereports/fl2pdf
accessed February 27, 2004

Agency for
Healthcare Research and Quality AHRQ, 2001 AHRQ Quality
Indicators-Guide to Prevention Quality Indicators: Hospital Admission
for Ambulatory Care Sensitive Conditions, AHRQ Pub No 02-R0203
Rockville, MD: Agency for Healthcare Research and Quality, 2001
Available at: http://wwwqualityindicatorsahrqgov accessed February
20, 2004

Agency for Healthcare Research and Quality AHRQ, 2002 AHRQ Quality
Indicators-Guide to Inpatient Quality Indicators: Quality of Care in
Hospitals-Volume, Mortality and Utilization, AHRQ Pub No 02-R0204
Rockville, MD: Agency for Healthcare Research and Quality, 2002
Available at: http://wwwqualityindicatorsahrqgov accessed February
20, 2004

Agency for Healthcare Research and Quality AHRQ, 2003 AHRQ Quality
Indicators-Guide to Patient Safety Indicators, AHRQ Pub No 03-R203
Rockville, MD: Agency for Healthcare Research and Quality, 2002
Available at: http://wwwqualityindicatorsahrqgov accessed April 9,
2004

Agency for Healthcare Research and Quality AHRQ, 2003a National
Healthcare Quality Report Rockville, MD: US Department of Health
and Human Services

Agency
for Healthcare Research and Quality AHRQ, 2003b National
Healthcare Disparities Report: Executive summary Rockville, MD: US
Department of Health and Human Services

Agency for Healthcare Research and Quality AHRQ, 2003c Your guide to
choosing quality healthcare Available at:
http://wwwahcprgov/consumer/qnt/ accessed November 7, 2003

Agency for Healthcare Research and Quality AHRQ, 2004 MEPS Statistical
Brief 37: Trends in adult obesity in the United States, 1987 and
2001: Estimates for the noninstitutionalized population, age 20 to 64
Available at: http://wwwmepsahrqgov/papers/st37/stat37htm
accessed February 27, 2004

American Association of Health Plans/Health Insurance Association of
America AAHP/HIAA, 2003 The cost savings of disease management
programs: Report on a study of health plans Available at
http://wwwaahporg/Content/ContentGroups/Homepage_News/DM_Short_Report
doc accessed December 8, 2003

American Diabetes Association ADA, 2004a Clinical practice
recommendations 2004 Diabetes Care, 27:S1-S150

American Diabetes Association ADA, 2004b Standards of medical care for
patients with
diabetes mellitus Diabetes Care, 27 Jan, Suppl 1:S15-
35

Atkins R 2003 Diabetes disease management, DMAA Medicaid disease
management audio conferences Presentation: Passport health plan
Available at http://wwwdmaaorg/audio/ accessed December 12, 2003

Beaulieu N, Cutler D, Ho K, Horrigan D, Isham G 2003 The business case
for diabetes disease management at two managed care organizations: A
case study of HealthPartners and Independent Health Association New
York: The Commonwealth Fund Available at
wwwcmwforg/programs/quality/beaulieu_diabetesdiseasemanagement_610pd
f accessed on December 17, 2003

Brown S, Matthews T 2003 State officials guide to chronic illness
Lexington, KY: The Council of State Governments

Bridges to Excellence 2004 Diabetes care link for prospective
purchasers Available at:
http://wwwbridgestoexcellencecom/bte/diabetescarelink/gty_purchasers
htm accessed on February 26, 2004

California Medi-Cal Type 2 Diabetes Study Group 2004 Closing the Gap:
Effect of diabetes case management on glycemic control among low-
income ethnic minority populations: The California Medi-Cal type 2

diabetes study Diabetes Care, 27:95-103

Centers for Disease Control and Prevention CDC, 2004 CDC at a glance:
Diabetes: Disabling, deadly and on the rise Available at:
http://wwwcdcgov/nccdphp/aag/pdf/aag_ddt2004pdf accessed April 7,
2004

Centers for Disease Control and Prevention CDC, 2003a Data and trends:
Diabetes surveillance system: Available at:
http://wwwcdcgov/diabetes/statistics/prev/state/fig61994and2002htm
accessed November 10, 2003

Centers for Disease Control and Prevention CDC, 2003b National diabetes
fact sheet: general information and national estimates on diabetes in
the United States, 2003 Atlanta, GA: US Department of Health and
Human Services Available at wwwcdcgov/diabetes/pubs/factsheethtm
accessed December 12, 2003

Centers for Disease Control and Prevention CDC, 2003c Diabetes: A
serious public health problem Available at
wwwcdcgov/nccdphp/bb_diabetes/ accessed December 17, 2003

Centers for Disease Control and Prevention CDC, 2003d Exemplary state
programs: Diabetes Available at
http://wwwcdcgov/nccdphp/exemplary/diabeteshtm accessed December
17, 2003

Centers
for Disease Control and Prevention CDC, 1999 Framework for
program evaluation in public health Morbidity and Mortality Weekly
Report 48 No RR-11

Cohen J, Krauss N 2003 Spending and service use among people with the
fifteen most costly medical conditions Health Affairs, 222:129-138

Cornell E 2003 State efforts to prevent and manage diabetes Washington,
DC National Governors Association: Center for Best Practices: Health
Policy Studies Division Available at:
http://wwwngaorg/cda/files/IBDIABETES020802pdf accessed November
6, 2003

Daniel D, Norman J, Davis C, Lee H, Hindmarsh M, McCullough D, Wagner E,
Sugarman J 2004 A State-level application of the chronic illness
breakthrough series: Results from two collaboratives on diabetes in
Washington State Joint Commission Journal of Quality and Safety
302:103-8,57

Diabetes Control and Complications Trial Research Group DCCT, 1990
Diabetes control and complications trial update Diabetes Care, 13:427-
33

Diabetes Control and Complications Trial Research Group DCCT, 1993 The
effect of intensive treatment of diabetes on the development and
progression
of long-term complications in insulin-dependent diabetes
mellitus New England Journal of Medicine, 32914977-986

Diabetes Control and Complications Trial Research Group DCCT, 1996
Lifetime benefits and costs of intensive therapy as practiced in the
diabetes control and complications trial Journal of the American
Medical Association, 27617:1409-15

Diabetes Prevention Program Group DPP, 2003 Within-trial cost-
effectiveness of lifestyle intervention or metformin for the primary
prevention of type 2 diabetes Diabetes Care, 269:2518-23

Faulkner L 2003 Disease Management: The new tool for cost containment
and quality care Washington, DC National Governors Association:
Center for Best Practices: Health Policy Studies Division Issue
Brief, p9
Available at: http://wwwngaorg/cda/files/031403DISEASEMGMTpdf
accessed November 10, 2003

Ford E, Williamson D, Liu S 1997 Weight change and diabetes incidence:
Findings from a national cohort of US adults American Journal of
Epidemiology, 1463:214-22

Freid V, Prager K, MacKay A, Zia H 2003 Health, United States, 2003:
Chartbook on trends in the health of Americans
Hyattsville, MD:
Center for Disease Control and Prevention, National Center for Health
Statistics Available at: wwwcdcgov/nchs/hushtm accessed December
17, 2003

Gabor A 2004 Running a hospital like a factory, in a good way New
York Times, Section 3: Money and Business, page 4, February 22, 2004

Haffner S, Lehto S, Ronnemaa T, Pyorala K, Laakso M 1998 Mortality from
coronary heart disease in subjects with type 2 diabetes and in
nondiabetic subjects with and without prior myocardial infarction New
England Journal of Medicine, 3394:229-34

Hawkins D, Proser M 2004 A Nations health at risk: A national and
State report on Americans 36 million people without a regular health
care provider Special Topics Issue Brief 5 Washington, DC:
National Association of Community Health Centers, 2004

Herman W, Eastman R 1998 The effects of treatment on the direct costs of
diabetes Diabetes Care, 21Suppl 3: C19-C24

Health Disparities Collaborative 2004 Available at
http://wwwhealthdisparitiesnet/abouthtml accessed April 7, 2004

Hogan P, Dall T, Nikolov P 2003 Economic costs of diabetes in the US
in 2002 Diabetes Care,
263:917-32

Institute for Healthcare Improvement IHI, 2002 Health disparities
collaboratives: Changing practice, changing lives: Diabetes training
manual Boston: IHI Available at:
http://wwwhealthdisparitiesnet/Diabetes_Apr2002pdf accessed
February 27, 2004

Institute of Medicine, Committee on Quality of Healthcare in America IOM,
2001a Crossing the quality chasm: A new health care system for the
21st century Washington, DC: National Academy Press

Institute of Medicine, Committee on the National Quality Report on health
Care Delivery IOM, 2001b Envisioning the National Healthcare
Quality Report Washington DC: National Academies Press

Institute of Medicine , Committee on the Consequences of Uninsurance, Board
on Health Care Services IOM, 2001c Coverage Matters: Insurance and
health care Washington, DC: National Academies Press

Institute of Medicine, Committee on Rapid Advance Demonstration Projects:
Health Care Finance and Delivery Systems IOM, 2002 Fostering rapid
advances in health care: Learning from system demonstrations
Washington DC: National Academies Press

Institute of Medicine IOM, 2003aThe
Richard and Hinda Rosenthal Lectures
2002: Fostering rapid advances in health care Washington, DC:
National Academy Press

Institute of Medicine, Committee on Understanding and Eliminating Racial
and Ethnic Disparities in Health Care: Board on Health Sciences Policy
IOM, 2003b Unequal treatment: confronting racial and ethnic
disparities in health care Washington DC: National Academies Press

Karter A, Ferrara A, Liu J, Moffet H, Ackerson L, Selby J 2002 Ethnic
disparities in diabetic complications in an insured population
Journal of the American Medical Association, 28719:2519-27

Keating N, Landrum M, Landon B, Ayanian J, Borbas C, Guadagnoli E 2003
Managing chronic illness in managed care settings: Measuring the
quality of diabetes care using administrative data: Is there a bias?
Health Services Research, 386:1529-45

Klonoff D, Schwartz D 2000 An economic analysis of interventions for
diabetes Diabetes Care, 233:390-404

Knowler W, Barrett-Connor E, Fowler S, Hamman R, Lachin J, Walker E, Nathan
D 2002 Reduction in the incidence of type 2 diabetes with lifestyle
intervention or metformin New England
Journal of Medicine, 3466:393-
403

Langley G, Nolan K, Nolan T, Norman C, Provost L 1996 The Improvement
Guide: A Practical Approach to Enhancing Organizational Performance
San Francisco: Jossey-Bass Publishers p 6-11

Leatherman S, Berwick D, Iles D, Lewin L, Davidoff F, Nolan T, Bisognano M
2003 The business case for quality: Case studies and an analysis
Health Affairs, 222:17-30

Lorig, K, Ritter P, Stewart A, Sobel D, Brown B, Bandura A, Gonzales V,
Laurent D, Holman H 2001 Chronic disease self-management program:
Two-year health status and health care utilization outcomes Medical
Care, 3911:1217-23

MacColl Institute for Healthcare Innovation, Group Health Cooperative
2004 The Chronic Care Model: Model Elements Available at:
http://wwwimprovingchroniccareorg/change/model/componentshtml
accessed April 26, 2004

McGlynn E, Asch S, Adams J, Keesey J, Hicks J, DeCristofaro A, Kerr E
2003 The quality of health care delivered to adults in the United
States New England Journal of Medicine, 348 26:2635-45

McNeill D, Kelley E 2004 How the National Healthcare Quality and
Disparities Reports can
catalyze quality improvement Rockville, MD:
US Department of Health and Human Services, Agency for Healthcare
Research and Quality Journal submission: February 2004

Missouri Department of Health and Senior Services 2002 Diabetes in
Missouri: Selected results from the 1988-2001 Mo-BRFSS Jefferson
City, MO: Department of Health and Senior Services, Diabetes
Prevention and Control Program

Mokdad A, Ford E, Bowman B, Dietz W, Vinicor F, Bales V, Marks J 2003
Prevalence of obesity, diabetes, and obesity-related health risk
factors, 2001 Journal of the American Medical Association, 2891:76-
79

Mokdad A, Ford E, Bowman B, Nelson D, Engelgau M, Vinicor F, Marks J
2000 Diabetes trends in the US: 1990-1998 Diabetes Care
239:1278-83

Mukhtar Q, Murphy D, Mitchell P 2003 Use of data from the behavioral
risk factor surveillance system optional diabetes module by States
Journal of Public Health Management and Practice, NovSuppl:S52-55

Narayan K, Boyle J, Thompson T, Sorensen S, Williamson D 2003 Lifetime
risk for diabetes mellitus in the United States Journal of the
American Medical Association,
29014:1884-90

National Conference of State Legislatures NCSL, 2003 State disease
management program descriptions Denver, CO Available at:
http://wwwncslorg/programs/health/StateDiseasemgmt1htm accessed
November 7, 2003

National Committee for Quality Assurance NCQA, 2003 The state of health
care quality 2003: Industry trends and analysis Washington, DC:
National Committee for Quality Assurance Available at
http://wwwncqaorg/Communications/State20Of20Managed20Care/SOHCREPO
RT2003pdf accessed April 7, 2004

National Diabetes Education Program NDEP, undateda Health care
providers toolkit: Small steps big rewards; Your game plan for
preventing type 2 diabetes Available at:
http://wwwndepnihgov/diabetes/pubs/GP_Toolkitpdf accessed
November 10, 2003

National Diabetes Education Program NDEP, undatedb Special needs for
special problems: Diabetes in women, children, the elderly, and
minority populations p132-3 Available at:
http://wwwniddknihgov/federal/dwg/2002/10womenpdf accessed
October 22, 2003

National Diabetes Information Clearinghouse NDIC, undated Your guide to
diabetes: Type 1 and
type 2: What diabetes is Bethesda, MD: National
Institutes of Health, National Institute of Diabetes and Digestive and
Kidney Diseases Available at:
http://wwwdiabetesniddknihgov/dm/pubs/type1and2/indexhtm
accessed November 7, 2003

Nelson D, Holtzman D, Bolen J, Stanwyck C, Mack K 2001 Reliability and
validity of measures from the behavioral risk factor surveillance
system BRFSS Sozial un Praventivmedizin, 46Supp 1:S3-42

Norris S, Nichols P, Caspersen C, Glasgow R, Engelgau M, Isham G, Snyder S,
Carande-Kulis V, Garfield S, Briss P, McCulloch D 2002 The
effectiveness of disease and case management for people with diabetes:
A systematic review American Journal of Preventive Medicine, 224
Supp:15-38

Norris S, Engelgau M, Narayan K 2001 Effectiveness of self-management
training in type 2 diabetes: a systematic review of randomized
controlled trials Diabetes Care, 243:561-87

Pan X, Li G, Hu Y, Wang J, An Z, Hu Z, et al 1997 Da Qing IGT and
diabetes study: Effects of diet and exercise in preventing NIDDM in
people with impaired glucose tolerance Diabetes Care, 20 4: 537-44

Resnick H, Valsania P,
Halter J, Lin X 2000 Relation of weight gain and
weight loss on subsequent diabetes risk in overweight adults Journal
of the Epidemiology of Community Health, 548:596-602

Safran M, Mukhtar Q, Murphy D 2003 Implementing program evaluation and
accountability for population health: Progress of a national diabetes
control effort Journal of Public Health Management and Practice,
91:58-65

Shojania K, McDonald M, Wachter R, Owens D 2004 Closing the quality gap:
A critical analysis of quality improvement strategies Volume1-Diabetes
mellitus and hypertension University of California, San Francisco-
Stanford Evidence-based Practice Center Contract No 290-02-0017

Sidorov J, Shull R, Tomcavage J, Girolami S, Lawton N, Harris R 2002
Does diabetes disease management save money and improve outcomes? A
report of simultaneous short-term savings and quality improvement
associated with a health maintenance organization-sponsored disease
management program among patients fulfilling health employer data and
information set criteria Diabetes Care, 254:684-9

Smith V, Ellis E, Gifford K, Ramesh R, Wachino V 2002 Medicaid
spending
growth: Results from a 2002 survey Washington, DC: Kaiser Commission
on Medicaid and the Uninsured Available at
http://wwwkfforg/medicaid/4064-indexcfm accessed December 17,
2003

Tague N The Quality Toolbox Milwaukee, WI: ASQC Quality Press, 1995

Tortorella M 1995 The three careers of W Edwards Deming The W Edwards
Deming Institute: Siam News, July 16, 1995 Available at:
http://wwwdemingorg/theman/articles/articles_threecareers01html
accessed December 17, 2003

Tuomilehto J, Lindstrom J, Eriksson JG, Valle TT, Hamalainen H, Ilanne-
Parikka P, Keinanen-Kiukaanniemi S, Laakso M, Louheranta A, Rastas M,
Salminen V, Uusitupa M 2001 Finnish Diabetes Prevention Study
Group: Prevention of type 2 diabetes mellitus by changes in lifestyle
among subjects with impaired glucose tolerance New England Journal of
Medicine, 34418:1343-50

UK Prospective Diabetes Study Group 1998 Tight blood pressure control
and risk of macrovascular and microvascular complications in type 2
diabetes British Medical Journal, 3177160:703-13

US Department of Health and Human Services DHHS, 2000 Healthy People
2010
2nd ed With understanding and improving health and objectives
for improving health 2 vols Washington, DC: US Government Printing
Office Available at: http://wwwhealthypeoplegov/ accessed November
10, 2003

US Department of Health and Human Services DHHS, 2003b HHS approves
new services for Indiana Medicaid enrollees with chronic diseases
Available at: http://wwwhhsgov/news/press/2003pres/20030602bhtml
accessed June 17, 2003

Wagner E, Austin B, Davis C, Hindmarsh M, Schaefer J, Bonomi A 2001
Improving chronic illness care: Translating evidence into action
Health Affairs, 206:64-78

Wheatley, B 2001 Medicaid disease management: Seeking to reduce spending
by promoting health State Coverage Initiatives Issue Brief Available
at: http://statecoveragenet/pdf/issuebrief0801pdf accessed February
27, 2004

Williams D 1999 Race, socioeconomic status, and health: The added
effects of racism and discrimination In Adler et al eds,
Socioeconomic Status and Health in Industrial Nations New York: New
York Academy of Sciences, 1999

Wisconsin Department of Health and Family Services 2003 The Wisconsin

collaborative diabetes quality improvement project, 2003 Available
at:
http://wwwdhfsstatewius/health/diabetes/pdf_files/DiabHMO_Collab200
3pdf accessed on December 17, 2003

Appendix A: Acronyms Used in This Resource Guide

AAHP/HIAA American Association of Health Plans/Health Insurance
Association of America
ADA American Diabetes Association
AHCA Agency for Health Care Administration of Florida
AHRQ Agency for Healthcare Research and Quality
AHRQ QIs AHRQ Quality Indicators
AMA American Medical Association
BRFSS Behavioral Risk Factor Surveillance System
BPHC Bureau of Primary Health Care of HRSA
CDC Centers for Disease Control and Prevention
CHC Community Health Center
CMS Centers for Medicare Medicaid Services
CSG Council of State Governments
CPS Current Population Survey
DCCT Diabetes Control and Complications Trial
DDI Diabetes Detection Initiative of Michigan
DHHS US Department of Health and Human Services
DON Diabetes Outreach Network of Michigan
DPCP Diabetes Prevention and Control Program joint CDC/State program
DQIP Diabetes Quality Improvement Program
FQHC Federally Qualified Health Centers
HDL High density
lipoproteins
HCUP Healthcare Cost and Utilization Project
HEDIS Health Plan and Employer Data and Information Set
HP2010 Healthy People 2010 of NIH and CDC
HRSA Health Resources and Services Administration
ICIC Improving Chronic Illness Care
IHI Institute for Healthcare Improvement
IHS Indian Health Services
IOM Institute of Medicine
JCAHO Joint Commission on Accreditation of Healthcare Organizations
MEPS Medical Expenditure Panel Survey
MSA Metropolitan Statistical Area
NCSL National Conference of State Legislatures
NCQA National Committee for Quality Assurance
NDCP National Diabetes Control Program
NDPCP National Diabetes Prevention and Control Program
NDEP National Diabetes Education Program
NDIC National Diabetes Information Clearinghouse
NDQIA National Diabetes Quality Improvement Alliance;
the NDQIA includes AHRQ, American Academy of Family Physicians;
American Association of Clinical Endocrinologists; American College
of Physicians; American Diabetes Association; American Medical
Association; Centers for Disease Control and Prevention; Centers for
Medicare Medicaid Services; Joint Commission on Accreditation of

Healthcare Organizations; National Committee for Quality Assurance;
National Institute of Diabetes and Digestive and Kidney Disease; The
Endocrine Society; US Department of Veterans Affairs

NHIS National Health Interview Survey
NHANES National Health and Nutrition Examination Survey
NHDR National Healthcare Disparities Report
NHDS National Hospital Discharge Survey
NHQR National Healthcare Quality Report
NIH National Institutes of Health
PDSA Plan-Do-Study-Act
QIO Quality Improvement Organization of CMS
Appendix B: List of NHQR Data Sources, Including Those Supporting State
Estimates

The following is a list of the data sources assembled and used in the NHQR
Those sources in bold collect data and support analyses at the State
level, although they may or may not be available in the NHQR:

Behavioral Risk Factor Surveillance System BRFSS
Dialysis Facility Compare DFC
Healthcare Cost and Utilization Project HCUP
Health Plan Employer Data and Information Set HEDIS
HIV/AIDS Surveillance System
Medical Expenditure Panel Survey MEPS
Medicare Quality Monitoring System MQMS
Minimum Data Set MDS
National Ambulatory Medical
Care Survey NAMCS
National CAHPS Benchmarking Database NCBD
National Health and Nutrition Examination Survey NHANES
National Health Interview Survey NHIS
National Home and Hospice Care Survey NHHCS
National Hospital Ambulatory Medical Care Survey NHAMCS
National Hospital Discharge Survey NHDS
National Immunization Survey NIS
National Nosocomial Infections Surveillance NNIS
National Nursing Home Survey NNHS
National TB Surveillance System NTBSS
National Vital Statistics System -Linked Birth and Infant Death Data
NVSS-I
National Vital Statistics System, Mortality NVSS-M
Outcome and Assessment Information Set OASIS
Quality Improvement Organization QIO
Surveillance, Epidemiology, and End Results Program SEER
United States Renal Data System USRDS

Appendix C: Additional Data Resources Related to Diabetes Care Quality

This appendix contains additional information and detailed tables on the
following:

National Healthcare Quality Report measures selection process

Table C1: Diabetes measure set for the NHQR with endorsing
organizations, data sources, and level of data

Descriptions of
data sources for the process and outcome measures
discussed in this Resource Guide including notable differences between
MEPS and BRFSS national rates and data tables from the NHQR

Table C2: Percent of non-institutionalized adults over age 18 saying
they were diagnosed with diabetes who reported having important tests
in the past year or two years in one case, by national population
subgroup, United States, 2000

Table C3: Percent of adults age 18 and over with diagnosed diabetes
who have specific HbA1c levels and who have specific blood pressure
levels, United States, 1999-2000

Table C4: Hospital admission for adults over age 18 for specific
diabetes complications excluding obstetric and neonatal admissions
and transfers from other institutions per 100,000 population age 18
and older, Healthcare Cost and Utilization Project HCUP, United
States, 2000

Table C5: Lower extremity amputations in persons with diabetes per
1,000 population all ages, National Hospital Discharge Survey,
United States, 1997-2000

Table C6: CDC Three-Year Baseline: Percent of adults age 18 and

over with diabetes who had recommended diabetes tests in the past
year, pooled 1997-1999

Table C7: CDC Annual Trends: Percent who had a dilated-eye examination
in the past year per 100 adults with diabetes, crude rates and age-
adjusted rates, by State, 1995-2002

Table C8: CDC Annual Trends: Percent who had a foot examination in
the past year per 100 adults with diabetes, crude rates and age-
adjusted rates, by State, 1995-2002

Table C9: CDC Annual Trends: Percent who had an influenza vaccination
in the past year per 100 adults with diabetes, crude rates and age-
adjusted rates, by State, 1995-2002

Flow chart of steps for estimating State Medicaid spending on diabetes
care

Figure C1: Estimation steps for Medicaid spending on diabetes care

National Healthcare Quality Report Measures Selection Process

Researchers have developed health care quality measures based on scientific
evidence, practice guidelines, and consensus processes Consensus building
around measure sets has been used recently to narrow the list of measures
and increase their acceptance

Consensus building is a process by which stakeholders
and experts in a
field identify a connection between a measure and quality health care The
process generally includes expert judgment and evaluation, rigorous testing
of the measure in the field to ensure that improved performance is linked
to improved health, and review and agreement of the experts Several
organizations are involved in developing national quality measure sets,
including:

The National Diabetes Quality Improvement Alliance discussed in
Module 4: Action
The National Quality Forum
The National Committee on Quality Assurance, the accrediting body for
managed care health plans, with its HEDIS performance measures

In the first NHQR, AHRQ pursued a careful process to define the first set
of NHQR measures The underlying framework for selecting the NHQR measure
set was developed by the Institute of Medicine in Envisioning the National
Health Care Quality Report Their matrix framework crosses components of
health system quality effectiveness, safety, timeliness, and patient
centeredness with consumers health care needs staying healthy, getting
better, living with illness or disability, and end-of-life care Measures
were chosen to fill the
cells of this matrix so that all areas of health
care quality would be addressed The measure selection process:

1 Invited organizations with consensus-based measures developed with
experts and often rigorous testing to submit them for review

2 Issued a public call for measures and data sources

3 Convened a Federal Interagency Workgroup to evaluate based on
importance, scientific soundness and feasibility the 600 measures
submitted and to select the final set of 147 measures

4 Invited public review of the final measure set

Out of the set of 147 measures in the NHQR, 12 are diabetes measures All
diabetes measures were developed through consensus processes of the
endorsing organizations Table C1 below lists the NHQR diabetes measures,
the organizations that endorse them through a consensus process, the data
sources, and the analytic level State or national supported by the data

Key: AHRQAgency for Healthcare Research and Quality; AMA American
Medical Association; BRFSSBehavioral Risk Factor Surveillance System;
HCUPHealthcare Cost and Utilization Project; HP2010Healthy People 2010;
JCAHO Joint Commission on Accreditation of Healthcare Organizations;
NCQANational Committee for Quality Assurance;
NDQIANational Diabetes
Quality Improvement Alliance; NHANESNational Health and Nutrition
Examination Survey; NHDS National Hospital Discharge Survey
Data Source Description, Limitations, and Data Tables From the NHQR

Notable Differences Between MEPS and BRFSS National Rates

Some of the MEPS and BRFSS measures on diabetes are the same and both are
used in the NHQR However, only one MEPS measure is used in this Resource
Guide because not only does MEPS not give State-level estimates, the
methods used to derive the MEPS and BRFSS estimates for the same measures
differ As a result, the NHQR diabetes estimates from MEPS and BRFSS show
notable differences for the HbA1c and immunization measures MEPS reports
that 90 percent of people with diabetes get one or more HbA1c test per
year; BFRSS reports 79 percent MEPS reports 55 percent of people with
diabetes receive a flu vaccination; BRFSS reports 37 percent MEPS and
BRFSS are very close on the eye and foot examination rates, 67 versus 67
percent and 66 versus 65 percent, respectively

The difference for the HbA1c test rate is in part due to the structure of
the survey questions and in part due to the treatment of respondents
who
have not heard of HbA1c While BRFSS allows for this distinction to be
made in the response options, MEPS does not These respondents are counted
as though they answered no in BRFSS, and potentially not included in
MEPS The percentage of these responses in BRFSS is fairly low, at about
5 in 2001, but will still affect the final rate

The difference for influenza immunizations is due to definitional
differences between BRFSS and MEPS The BRFSS rate is for adults age 18 to
64; the MEPS rate is for adults age 18 and over Since flu shots are more
often given to the elderly, the BRFSS rate is lower than the MEPS rate

There are other differences between the two data sources that can
contribute to the differences between estimates of the same measures The
surveys relate to different time periods, use different sampling
approaches, and use different interview techniques, to name the obvious
Because of the differences in the estimates of the same measures and
because only BRFSS permits State estimates, only BRFSS estimates are
discussed in Module 3: Information of this Resource Guide

Process Measures-MEPS data

The MEPS data provide national benchmarks by important segments of
the
population Its breakdowns identify subgroups for whom diabetes care
quality can be problematic and for whom solutions need to be targeted

Table C2 shows estimates for the five MEPS diabetes-related measures in
the NHQR The estimates are provided by national subgroups related to
race, ethnicity, sex, age, education, employment status, income, health
insurance status, respondents location, and perceived health status
Table C2 shows the rate per 100 respondents or percent and the standard
error for each measure and subgroup Only estimates that have a standard
error that is less than 30 percent of the estimate relative standard error
30 percent are shown on Table C2 No statistical comparison tests were
performed in Table C2 but the estimates and standard errors can be used to
make such comparisons see Appendix E for how to do this
|Table C2 Percent of non-institutionalized adults over age 18 saying they were|
|diagnosed with diabetes who reported having important tests in the past year or|
|two years in one case, by national population subgroup, United States, 2000 |
| | |HbA1c test |Lipid |Retinal eye|Foot |Influenza |
| |
|a/ |profile in |examination|examination|immunizatio|
| | | |past two | | |n |
| | | |years | | | |
|Population group |
|b/ Persons 18 and over with unknown education status not included |
|c/ Employment status for persons 18-64 only |
|d/ For all values, RSE 30 percent |
|DSU - Data do not meet the criteria for statistical reliability, data quality or|
|confidentiality |
|Source: Agency for Healthcare Research and Quality, Center for Financing, Access|
|and Cost Trends, Medical Expenditure Panel Survey |
Outcome Measures-NHANES, HCUP, and NHDS Data

NHANES Data

The NHQR uses data from the National Health and Nutrition Examination
Survey for two outcome measures related to diabetes-the HbA1c, a measure of
blood glucose level over the prior two to three months, and blood pressure
at examination NHANES does not
support State-level estimates but does
provide clinical outcome estimates for the total national population that
could be used as benchmarks [Note: To be comparable to data from
providers, the NHANES HbA1c and blood pressure values would have to be
recalculated to exclude people who do not use the health care system during
a year]

The NHANES collects data from in-person interviews, physical examinations,
and medical tests from a mobile vehicle which is set up as a medical
office With this survey method, NHANES is able to collect data that are
detailed clinically, including laboratory results Because of the expense
of the NHANES eg, the cost of the mobile clinic and staff, the sample
size on the NHANES is small, 9,965 participants, and does not support
either State-level estimates or national subgroup estimates within the
population of people with diabetes Additional information on NHANES is
available at: http://wwwcdcgov/nchs/about/major/nhanes/NHANES99_00htm

Table C3 shows the percent of adults with diabetes by specific test
values The percent and standard error are provided

In addition to the HbA1c and blood pressure values, NHANES can provide LDL-
C levels 130 mg/dL needs improvement and 100 optimal Those LDL
estimates were not available in time for publication of the first NHQR
The measure
remains part of the official NHQR measure set and is to be
included in the future

HCUP Data

The NHQR uses inpatient discharge abstract data from the Healthcare Cost
and Utilization Project for national estimates of three outcome measures
that provide a window on the quality of ambulatory care-avoidable
hospitalizations related to diabetes While the national estimates are
included in the NHQR, State-level data are not, except for one special
analysis of admissions for uncomplicated uncontrolled diabetes discussed
in Module 3: Information For year 2000 data used in the NHQR, 29 States
contributed and more States had statewide discharge data systems maintained
by State data agencies, State hospital associations, or statewide data
consortia These data systems can be used to generate these three outcome
measures
HCUP is a public-private partnership sponsored by AHRQ with 29
participating States in 2000, the time for which data are included in the
first NHQR The data are from statewide historical administrative
databases going back to 1988 In 2000, HCUP included the:
Nationwide Inpatient Sample NIS - all hospitals and all of their
inpatient discharges 6 to 7 million
records per year across the 29
States, weighted so that national estimates can be derived from it

State Inpatient Databases SID - a census of inpatient discharge
records for each participating State covering nearly 80 percent of the
36 million US hospital discharges per year in 2000

State Ambulatory Surgery Databases SASD - all discharge records for
ambulatory surgery centers hospital based and freestanding

Kids Inpatient Database KID - A sample of childrens discharges
from over 2,500 community hospitals
In addition, AHRQ developed the Quality Indicators, which are measures of
health care quality that make use of readily available hospital inpatient
administrative data and available as public software to help analysts
evaluate quality of care in hospitals and, indirectly, in ambulatory care
settings The AHRQ QIs are organized into three categories, the Prevention
Quality Indicators, the Inpatient Quality indicators, and the Patient
Safety Indicators Additional information on HCUP data is available at:
http://wwwhcup-usahrqgov/databasesjsp Additional information on the
AHRQ QIs is available at:
http://wwwqualityindicatorsahrqgov/
The NHQR and NHDR used selected Prevention Quality Indicators to examine
hospital admissions that evidence suggests could have been avoided, at
least I part, through high-quality outpatient care Table C4 shows rates
of three of these indicators related to diabetes-hospital admissions for
three complications of diabetes that should be avoidable-1 uncontrolled
uncomplicated diabetes, 2 serious short-term complications, and 3 serious
long-term complications The rates are defined relative to 100,000 people
in the population of the State Results are presented by patient
characteristics age, sex, income, and location of patient residence and
by hospital characteristics region of the country The rate and its
standard error are shown
The main limitation of HCUP data or any other administrative data source
is that the data are collected for one purpose and used for another Many
State-level discharge data systems use data from hospital billing data and
are thus collected for reimbursement purposes However, these data are so
valuable that they are used for many other purposes, such as cost tracking,
quality monitoring, or health policy evaluations
Reimbursement incentives
affect what data are collected and how they are collected Thus, while
mining these data for clues to quality, analysts should constantly be on
the alert for data problems-incomplete or inaccurate entries or lack of
adequate clinical detail

|Table C4 Hospital admission for adults over age 18 for specific |
|diabetes complications excluding obstetric and neonatal admissions|
|and transfers from other institutions per 100,000 population age |
|18 and older, Healthcare Cost and Utilization Project, United |
|States, 2000 |
| |
| |For |For diabetes |For diabetes |
| |uncontrolled |with |with long-term|
| |diabetes |short-term |complications |
| |without |complications |c/ |
| |complication |b/ | |
| |a/ | | |
|Population group |Estimat|Standa|Estimat|Standa|Estimat|Standa|
| |e d/ |rd
|e d/ |rd |e d/ |rd |
| | |error | |error | |error |
|Total |28518 |1056 |51202 |1437 |120810|2922 |
|Patient | | | | | | |
|characteristic | | | | | | |
|Age groups | | | | | | |
| 18-44 |14698 |0658 |54179 |1749 |33484 |1203 |
| 45-64 |35765 |1570 |48693 |1560 |158036|4663 |
| 65 and over |59172 |2037 |45275 |1362 |338630|7922 |
|Age groups for | | | | | | |
|elderly | | | | | | |
| 65-69 |49147 |2428 |40031 |1931 |293116|8094 |
| 70-74 |57050 |2673 |40686 |1932 |336307|8931 |
| 75-79 |66926 |2988 |46638 |2165 |371110|10177|
| 80-84 |68099 |3339 |52712 |2705 |388835|11263|
| 85 and over |66566 |3643 |55424 |3290 |339067|11185|
|Gender | | | | | | |
| Male |28542 |1072 |53180 |1746 |135980|3215 |
| Female |28399 |1112 |49119 |1313
|108278|2853 |
|Median income of | | | | | | |
|patient zip | | | | | | |
| Less than 25,000 |62728 |5709 |91142 |7913 |193319|15735|
| 25,000-34,999 |42783 |2184 |66742 |3123 |150143|6530 |
| 35,000-44,999 |30324 |1720 |56531 |2586 |126912|5240 |
| 45,000 or more |16604 |0872 |37990 |1626 |90913 |3692 |
|Location of patient | | | | | | |
|residence | | | | | | |
| MSA e/ |25126 |1180 |51353 |1714 |116966|3349 |
| Non-MSA e/ |39697 |1895 |51859 |2056 |121337|5099 |
|Hospital | | | | | | |
|characteristic | | | | | | |
|Location of inpatient| | | | | | |
|treatment | | | | | | |
| Northeast |30106 |3489 |48082 |2826 |135812|8645 |
| Midwest |27987 |2266 |45444 |2948 |109735|5310 |
| South |35652 |1543 |61359 |2690 |133628|4595 |
| West |15610 |1158 |43313 |2806 |96239 |5363 |
|a/
Without short-term ketoacidosis, hyperosmolarity, coma or |
|long-term renal, eye, neurological, circulatory, other |
|unspecified complications |
|b/ Ketoacidosis, hyperosmolarity, or coma |
|c/ Renal, eye, neurological, circulatory, or other unspecified |
|complications |
|d/ Rates are adjusted by age and sex using the total US as the |
|standard population; when reporting is by age, the adjustment is by|
|sex only; when reporting is by sex, the adjustment is by age only |
| |
|e/ Metropolitan Statistical Areas |
|Source: Agency for Healthcare Research and Quality, Center for |
|Delivery, Organization, and Markets, Healthcare Cost and |
|Utilization Project, Nationwide Inpatient Sample 2000 |

NHDS Data

Table C5 shows the rate of lower extremity amputations for people with
diabetes per 1,000 population, for two time periods-1997 through 1999 and
1998 through 2000 NHDS pools data over several years, which is why the
tables
reflect an overlap in years The estimates are provided by national
subgroups when the size of the database supports the subgroup estimate
ie, for age, sex, and black-white subgroups The rate and standard
error of the rate are provided Each State with discharge data can
generate estimates for all of the subgroups reported
|Table C5 Lower extremity amputations in persons with|
|diabetes per 1,000 population all ages, National |
|Hospital Discharge Survey, United States, 1997-2000 |
| |1997-1999 |1998-2000 |
| | |Standa| |Standa|
| | |rd | |rd |
|Population group |Rate |error |Rate |error |
|Total |50 |04 |48 |04 |
|Age not age adjusted | | | | |
|0-17 |DSU |DSU |DSU |DSU |
|18-44 |33 |06 |35 |06 |
|45-64 |71 |06 |64 |06 |
| 65 and over |104 |07 |98 |07 |
|Race a/ | | | | |
|American Indian or Alaska |DSU |DSU |DSU |DSU |
|Native
| | | | |
|Asian or Pacific Islander |DSU |DSU |DSU |DSU |
| Asian |DSU |DSU |DSU |DSU |
| Native Hawaiian or |DSU |DSU |DSU |DSU |
|Other Pacific Islander | | | | |
|Black or African American |73 |15 |70 |15 |
|White |34 |03 |35 |04 |
|Ethnicity | | | | |
|Hispanic |DSU |DSU |DSU |DSU |
|Non-Hispanic |DSU |DSU |DSU |DSU |
| Black or African |DSU |DSU |DSU |DSU |
|American | | | | |
| White |DSU |DSU |DSU |DSU |
|Gender | | | | |
|Female |29 |03 |32 |03 |
|Male |73 |08 |66 |08 |
|Expected payment source b/| | | | |
|Medicaid |DSU |DSU |DSU |DSU |
|Medicare |DSU |DSU |DSU |DSU |
|Private/other insurance |DSU |DSU |DSU |DSU |
|Uninsured |DSU |DSU |DSU |DSU |
|Unknown weighted count
|DSU |DSU |DSU |DSU |
|a/ Race categories changed in 2000 Data for 2000 may |
|not be comparable to those used in previous years |
|b/ Rates may be overestimated due to undercount in the |
|denominators of some payment sources from the Current |
|Population Survey |
|DSU - Data do not meet the criteria for statistical |
|reliability, data quality, or confidentiality |
|Source: Centers for Disease Control and Prevention, |
|National Center for Health Statistics, National |
|Hospital Discharge Survey |
Table C6 CDC Three-year baseline: Percent of adults age 18 and over with
diabetes who had recommended diabetes tests in the past year, pooled 1997-
1999 a/

Table C7 CDC annual trends: Percent who had a dilated-eye examination in
the past year per 100 adults with diabetes, crude rates and age-adjusted
rates, by State, 1995-2002

Table C8 CDC annual trends: Percent who had a foot examination in the
past year per 100 adults with diabetes, crude rates and age-adjusted rates,
by State, 1995-2002

Table C9 CDC annual trends: Percent who had an
influenza vaccination in
the past year per 100 adults with diabetes, crude rates and age-adjusted
rates, by State, 1995-2002

Estimation Steps for Medicaid Spending on Diabetes Care by State

This section describes methods for estimating Medicaid spending on medical
care for people with diabetes by State

Estimates for Medicaid spending on diabetes care had to be constructed from
multiple public data sources, as described in Module 2: Data Because the
estimation involved many assumptions, the method used is described in a
flow chart Figure C1 The top level of the flow chart represents the
original data sources; the middle levels show assumptions, adjustments, and
calculations made with the original data; and the final level at the
bottom of the flow sheet is the result The adjustments were necessary to
make different sources compatible with respect to population and time
frame This method was applied to data on Medicaid eligibles to get an
estimate of the potential cost for Medicaid of medical care for diabetes
patients

These are only ball-park estimates because of the assumptions that had to
be made to work with available data Obvious limitations in these estimates
include
omission of spending for children and the institutionalized
population Furthermore spending on medical care unrelated to diabetes is
included when it should be excluded Although spending for children and
youth under age 20 is omitted, only 025 percent of this population has
diabetes and the effect is likely to be small The omission of the
institutionalized population is a more serious downward bias on spending
estimates because people with advanced stages of diabetes are more likely
to be hospitalized or to reside in nursing homes, and their care is costly
The inclusion of spending for all medical care for people with diabetes 20
years of age and over is included in these estimates rather than only the
spending related to diabetes because medical expenditures by type and age
could not be identified readily This overestimates expenditures related
to diabetes only

The resulting ball-park estimates are shown in Table 22 of the Resource
Guide Clearly, a better approach to deriving State Medicaid costs for
diabetes care would be to use Medicaid claims, if they were readily
available for all States
Figure C1 Estimation steps for Medicaid spending on diabetes care

Appendix
D: Benchmarks From The NHQR

More Details on Benchmarks
The NHQR provides a national set of estimates and often State estimates
that can be used as benchmarks for quality improvement A benchmark can be
a baseline or point from which you start, not necessarily representing a
goal or target Or it can be the best current rate, something achievable,
or a consensus of what should be achieved It is a basis for making
comparisons

Several types of benchmarks can be derived from the NHQR:

Theoretic limit benchmark: The theoretic limit refers to the maximum or
minimum level that a measure can take on; for example, 100 percent for
positive outcomes or 0 percent for negative, avoidable events In an
ideal world, these would be achievable, but in a world where so many
factors are involved in achieving a maximum result, those benchmarks may
be unrealistic Also, some concepts might feasibly come closer to the
theoretic limit than others

Best-in-class benchmark: The rate for the top State or top tier of
States can be used for what manufacturers call a best in class
benchmark The top tier can be defined as the top 5 or 10 percent of
States averaged
together Using influenza vaccination as an example,
the highest rate of flu vaccination for people with diabetes across the
States 64 percent may be assumed to be a feasible goal for States to
achieve However, some may view the top State rate as an impractical
target given their population and circumstances Others may view that
goal as inadequate, depending on the value of the rate and the state of
medical knowledge and practice, and they may view the 100-percent goal as
their target These judgments will vary across States because States
face different circumstances and environments This Resource Guide uses
the top 10 percent of States, combined in a simple average, to derive the
best-in-class estimate A simple average, rather than weighted average,
was used because the denominators from the BRFSS estimates were not
available in the NHQR

A national consensus-based goal: Some organizations propose targets that
should be achieved to improve the health status of the overall population
and vulnerable subgroups For example, two decades ago, the National
Center for Health Statistics of the Centers for Disease Control and

Prevention developed diabetes-related goals for a healthier US
population Each decade those goals are reviewed and reestablished The
current goals see inset of diabetes-related topics for Healthy People
goals, now called Healthy People 2010 HP2010, US Department of Health
and Human Services, 2000, also are included in the NHQR when relevant

The national average: The overall average indicates where the average
member of a group stands For example, the average of influenza
vaccination rates for people with diabetes in States 37 percent
according to the BRFSS data source is the norm for States or is the
rate for the average State States with rates below the average would
prefer to be at or above the average But the average may not be an
indicator of quality health care

The regional norm: States may prefer a regional estimate for comparison
because they want to see how they perform compared to medical practice
within the region Given the wide regional variation in US medical
practice Wennberg and Cooper, 1999, regional estimates may be weak
goals for regions where practice should change to enhance the health care
quality for
people with diabetes For this Resource Guide, the regional
averages are calculated for the four Census regions: Northeast, Midwest,
South, and West The averages are simple averages because the
denominators for BRFSS estimates were not available from the NHQR

The State rate: As noted in the Module 3: Information, the States own
rate may serve as a benchmark for various purposes-tracking changes over
time, evaluating the effect of a statewide intervention to improve
quality, or reporting the norm for local communities and providers to
compare to their own performance Concerns noted above about using
national or regional averages as goals also apply to State rates For
provider-level estimates, the best-in-class providers may be a better
indication of what is achievable and should be used as a goal rather than
the State average rate Severity adjustments are an important issue at
the provider level, where populations of patients with varying severity
and comorbidity levels are unlikely to be distributed evenly across
providers

The Best Benchmarks

Best-in-class estimates are the best way to view the opportunities for a
State to improve
Basing a best-in-class measure on a group of best States
rather than the single top State mitigates the effects of an extreme that
other States might find unreasonable to emulate

Table D1 shows values for the best-in-class benchmarks as simple averages
of the top 10 percent of States and for other benchmarks The other
benchmarks include Healthy People 2010 goals when available for a
measure, the national norm, regional average benchmarks, and State rates
for the four example States used in this Resource Guide These benchmarks
are provided for all of the diabetes-related measures in the NHQR Four of
the measures-HbA1c test, eye exam, foot exam, and flu vaccinations in the
past year in addition to HbA1c test two times in the past year-are
displayed graphically in the Module 3: Information

Benchmarks related to diabetes care for different socioeconomic groups are
available from the NHDR Those benchmarks are national averages and are
not available by State However, individual States may have data that can
be analyzed by socioeconomic group eg, avoidable hospitalizations by
racial, educational, or income group Table D2 shows values for the
national averages for diabetes process
and outcome measures by
socioeconomic characteristics of the national population

Methods Matter

Methods of measurement and data quality can have a large impact on the
value of a benchmark For this reason, it is crucial that the methods and
data used to derive various benchmarks are similar For example, when
comparing the State to the Nation, the same methods and data sources should
be used to calculate the estimates That is why this Resource Guide
presents only the BRFSS estimates to compare States and the Nation Other
sources for example MEPS were used for national estimates of the same
measures in the NHQR However, MEPS and BRFSS use different survey methods
and present different measures; the impact of the former is apparent in the
HbA1c rates-90 percent MEPS versus 79 percent BRFSS-and the impact of
the latter is seen in the influenza vaccination rates for people with
diabetes-55 percent for those age 18 and over MEPS versus 37 percent for
those age 18 to 64 BRFSS

Appendix E: Information on Statistical Significance

This section is provided for data analysts who want to generate other
statistics and/or perform statistical tests for
other comparisons than
those that are provided in the NHQR and NHDR

Comparing State and Average Estimates Using P-Values

When comparing an individual State estimate to another estimate, such as
the all-State average or the average for the top tier of States, every
measure has error associated with it The error is associated with
sampling size of the sample or sampling methods, accuracy of respondents
recall and responses, data entry processes, and many other factors When
comparing estimates it is important to take this error which can be
estimated with statistical assumptions into account

P-Values

A common statistic for comparing two rates to determine whether they differ
is the t-test based on a normal distribution The t-test can be compared
to a normal distribution with a pre-specified level of significance or
acceptable error in conclusions about whether or not two statistics come
from the same distribution or population The p-value, a statistic for a
normal distribution, can be calculated to determine whether two measures
are likely from the same or from different distributions

Judgments About Comparisons

Statistical significance and magnitude of the difference should
be
considered together when comparing two estimates The first check should
be: Is the difference statistically different? The second check should
be: Are the differences large enough to be meaningful for policy purposes?

Is the difference statistically different? Are the p-values less than
005? If so, you can assume that the underlying distributions come from
different populations or experiences But there are some other
considerations The statistical test of differences is affected by the
number of observations from which the measures were generated For
example, if the measures were generated from hundreds of thousands of
records then summary measures such as averages have less variance and
lower p-values, which imply statistical significance even when the
magnitude of the differences might be tiny Alternatively, when
differences are large and the number of observations is few, the absence
of statistical significance might simply mean that the data set does not
have enough observations for a powerful test This happens frequently
with the BRFSS measures because the annual sample sizes of the State
surveys are small-from about
2,000 to 8,500 observations

Are the differences large enough to be meaningful for policy purposes?
Because of the relationship between the statistical test and the number
of observations, some judgment must be used to assess the meaning of the
differences between State estimates Thus, in addition to statistical
significance, it is important to ask the second question: Is the State-
to-benchmark difference large enough to warrant efforts to rectify it? A
1- or 2-percentage-point difference in a measure may not be worth the
effort to improve it A 5- or 10-percentage-point difference may mean
that a substantial number of State residents are affected by poor health
care quality in the State These are judgments that local experts and
stakeholders who understand the environment of a State can help make

How To Calculate P-Values

P-values are used in this Resource Guide to determine whether the estimate
of a given State is statistically different-above or below a given average
eg, the national average or the average of the top decile States
Calculating the p-value is straightforward when the standard errors SEs
of the estimates are provided, as in
the case of the national rate and
individual State rates in the first formula and example below However,
when the standard error has not been provided, as is the case for the mean
of the top decile of States, then the calculation is more complicated and
may require additional data, such as sample sizes The method for the p-
value calculation for the top-decile States is also provided see second
formula and example

Calculating P-Value To Compare States to the National Average

For an individual State estimate compared to the national average, the
following formula shows how to derive a t-test statistic, which is a
statistical test for whether the State average is likely to come from a
distribution different from the national average From the t-test, a p-
value can be derived; and if the p value is less than 005, it can be
concluded with 95-percent confidence that the mean from the State
distribution is statistically different from the mean from the national
distribution see example for one State Rates and standard errors are
provided for most measures in the NHQR tables

Two-sided t-test:

where:
R1 a State rate
R2 national rate
SE21 square
of the standard error of the State rate or its
variance
SE22 square of the standard error of the national rate or its
variance

This formula is more conveniently calculated using SAS or EXCEL with the
following commands:

SAS: p 2 1 - PROBNORMABSt

EXCEL: p 21 - NORMDISTABSt,0,1,TRUE

Example: How does Georgia compare to the national average for annual
retinal exams for adults with diabetes? The national rate and standard
error for adults with diabetes receiving annual retinal exams are 667 and
12, respectively Georgias rate and standard error for annual retinal
exams are 704 and 37, respectively Following is the EXCEL statement for
the p-value, which encompasses the t-test formula with the Georgia and
national values

p 21-NORMDISTABS704-
667/SQRT37371212,0,1,TRUE
p 034

Because the p-value is greater than 005, we cannot conclude that Georgia
is statistically different from the national average Our confidence is
that this would be true 95 percent of the time in repeated tests

Calculating P-Value To Compare States to the Top Decile Average

To compare individual States to the
top decile average, both the top decile
rate and its standard error must be estimated, which is done using the
fundamental equation of analysis of variance and weighting individual State
values by their respective samples sizes The NHQR tables do not provide
sample sizes; but this information is available from the CDC Web site

Let us assume that the top decile is comprised of three States Using the
three top States, the formula determines the three-State sample size, the
weighted mean for the three States, and the total sum of squares about the
three-State mean The latter is the sum of the within-State sum of squared
deviations from the State mean and the between-State sum of squared
deviations from the three-State mean The within-State sum of squares SS
is obtained by squaring the States SE and multiplying by the sample size
times the sample size minus one The between-State sum of squares is
obtained by summing the sample-weighted squared difference between the
State mean and the overall three-State mean Here is the formula note:
sqrtx square root of x:

Let n1, n2, and n3 be the sample sizes for each State
Let m1, m2, and m3 be the means for each
State
Let s1, s2, and s3 be the standard errors for each State
N n1 n2 n3, is the overall three-State sample size
M n1m1 n2m2 n3m3 / N, is the overall three-State
mean
Within State SS n1n1-1s12 n2n2-1s22 n3n3-1s32,
represents the simplified sum of squared deviations
of values within the State from its mean
Between State SS n1m1-M 2 n2m2-M 2 n3m3-M2, is
the sum of squared deviations of means between the
three States weighted by sample size
Total SS Within State SS Between State SS
VAR SS/N-1, is the estimated variance for the three-State
mean
SE sqrtVAR/N, is the estimated standard error for the three-
State mean

Using the estimated standard error and weighted mean for the top decile of
States, a p-value can be calculated that reflects how a State compares to
the average of top decile States

Example: How does Georgia compare to the top decile of States for rates of
annual retinal exams for adults with diabetes? First, determine the number
of States
in the top decile If all States are considered, then the top
decile would be the top five States, however, not all States report for all
data sources In the case of BRFSS data for diabetes, 41 States and the
District of Columbia reported; therefore, the top decile is the top four
States

The four States with the highest rates for retinal eye exams are Wisconsin
with a rate of 825, SE31, and sample size of 201; Maine with a rate of
823, SE35, and a sample size of 172; Nebraska with a rate of 804,
SE56, and a sample size of 214; and Connecticut with a rate of 771,
SE43, and a sample size of 492 The overall sample size is 1,079 and the
overall weighted average is 796 The within State SS6,642,737, the
between State SS6,156, and the total SS6,648,893 From the total SS, the
weighted SE can be determined for the top decile average and the
calculation for p-values can be used to compare States to that top decile
average

The p-value for Georgia compared to the top decile average is 003
Because the p-value is less than 005, it can be concluded that Georgia,
which is below the top-decile average, is significantly different from the
top decile and, thus, there is opportunity for
improvement in annual
retinal exams
Appendix F: NHQR Quality Measures for All Conditions by State

This appendix lists quality measures for all conditions and topics in the
NHQR It includes the national estimate and then an indicator for whether
or not the State estimate not shown due to space limitation is
statistically greater, lower, or no different from the national average
The measures for which State-level data are not reported in the NHQR are
noted as not available n/a This resource can help States identify which
diseases and treatments, including and outside of diabetes, may be in need
of attention Many of the same data issues described in Module 2: Data and
Module 3: Information are applicable to other disease topics, although
different data sources and limitations may apply to them
Table F1 NHQR quality measures for all conditions when available by
State, alphabetically Alabama through Missouri

See Footnotes at the end of Table F2

Table F2 NHQR quality measures for all conditions when available by
State, alphabetically Montana through Wyoming

a/ Symbols for significance test are:
greater than national average and statistically
significant at the p005 level
- less than national average and statistically significant
at the p005 level
ns not significant ie, not statistically different
than the national average
n/a either the national or State rate or standard
error was not available
b/ Measure is age adjusted to the 2000 standard population
c/ 1990-based postcensal population estimates were used to calculate
death rates; future reports will present rates based on intercensal
population estimates for 1998 and 1999 and bridged-race population
estimates for 2000 and subsequent years
d/ Population includes males only

e/ Population includes females only
f/ Prevalent dialysis patients on list on 12/31/YR divided by prevalent
dialysis patients on 12/31/YR
g/ All Medicare dialysis patients who initiated therapy in the given year
were included
h/ Patients with prior kidney transplants and patients over the age of 69
were excluded from the measure
i/ Percents are estimated using the Kaplan-Meier methodology
j/ Follow-up is censored at removal from the list, death, or the end of
the three year period
k/ Patient survival rate is measured as standardized mortality ratio
SMR by source of the data
l/ Population is Medicare patients only
m/ Time in minutes from arrival to initiation of a thrombolytic agent in
patients with ST segment elevation or left bundle branch block LBBB
on the electrocardiogram ECG performed closest to hospital arrival
time
n/ Median time in minutes from arrival to percutaneous transluminal
angioplasty PTCA in patients with ST segment elevation or left
bundle branch block LBBB on the electrocardiogram ECG performed
closest to hospital arrival time
o/ Includes only those with liveborn
infants
p/ Percent of children, age 19 to 35 months, receiving at least four
doses of diphtheria-tetanus-acellular pertussis DTaP, at least three
doses of polio, at least one dose of measles-mumps-rubella MMR, at
least three doses of Haemophilus influenzae B Hib, and at least
three doses of hepatitis B antigens
q/ Pain during a 7 day period that was excruciating at any time or
moderate, among residents experiencing daily pain
r/ For period 4/1/02 to 6/30/02
s/ A facility had to have at least 20 residents in the denominator for a
post-acute measure to be calculated and 30 residents in the
denominator for a chronic care measure to be calculated Therefore
the number of facilities may vary for each measure reported in a
State
t/ At least 1 of 4 late-loss ADLs bed mobility, transfers, toilet use
and eating
u/ This percentage is composite of data from the quarterly and annual MDS
assessment forms completed for residents The annual MDS form
contains data on multiple types of infections
v/ US estimate reflects the average of the States with measures
w/ For period 1/1/02 to 6/30/02
x/
Consumer language used on the Home Health Compare Web site for this
measure is: Percentage of patients who get better at getting dressed
y/ Consumer language used on the Home Health Compare Web site for this
measure is: Percentage of patients who get better at taking their
medicines correctly by mouth
z/ Consumer language used on the Home Health Compare Web site for this
measure is: Percentage of patients who get better at bathing
aa/ Consumer language used on the Home Health Compare Web site for this
measure is: Percentage of patients who stay the same or dont get
worse at bathing
ab/ Consumer language used on the Home Health Compare Web site for this
measure is: Percentage of patients who get better at getting in and
out of bed
ac/ Consumer language used on the Home Health Compare Web site for this
measure is: Percentage of patients who get better at walking or
moving around
ad/ Consumer language used on the Home Health Compare Web site for this
measure is: Percentage of patients who get better at getting to and
from the toilet
ae/ Consumer language used on the Home Health Compare Web
site for this
measure is: Percentage of patients who have less pain when moving
around
af/ Consumer language for this measure is: Percentage of patients who are
short of breath less often The CMS report results of testing this
language is available at
http://wwwcmshhsgov/quality/hhqi/OASISPhaseIpdf
ag/ Consumer language for this measure is: Percentage of patients who are
having less of a problem with urinary incontinence or wetting
themselves The CMS report results of testing this language is
available at http://wwwcmshhsgov/quality/hhqi/OASISPhaseIpdf
ah/ Consumer language used on the Home Health Compare Web site for this
measure is: Percentage of patients who are confused less often
ai/ Consumer language used on the CMS Home Health Compare Web site for
this measure is: Percentage of patients who had to be admitted to the
hospital
aj/ The national average includes Puerto Rico
ak/ The national average includes the Virgin Islands
al/ The national average includes Guam
Appendix G: Index of Diabetes Quality Improvement Initiatives

Listed below are a number of national and Federal quality
improvement
programs related to diabetes that State leaders may find useful as
templates for State initiatives or for additional resources

Public/Private Quality Improvement Initiatives

There are a wide range of public and private quality improvement
initiatives active at different stages of quality improvement While there
are numerous components of quality improvement, the examples given below
illustrate the quality improvement activities aimed at measurement and
incentives While the list is by no means exhaustive of public/private
quality improvement initiatives, it provides examples of what organizations
are doing specific to diabetes

Measurement

National Committee for Quality Assurance and HEDIS Measures

The National Committee for Quality Assurance is a national, nonprofit
organization founded in 1991 that is dedicated to improving the quality of
health care NCQA is well known for its accreditation of managed care
organizations and performance measurement initiatives NCQAs Health Plan
Employer Data and Information Set or HEDIS is used by more than 90
percent of health plans in the United States to report performance on a
wide variety of quality of care indicators,
ranging from child immunization
rates to waiting time for appointments to member satisfaction measures
HEDIS also includes measures for diabetes care quality NCQA reports on
health plan performance in its annual publication, the State of Health Care
Quality NCQA, 2003 In addition, NCQAs Quality Compass, a national
database of HEDIS and accreditation information from health plans, is a
resource for health plans, employers, and governments to assess and compare
health care quality NCQA in collaboration with the American Diabetes
Association also has a program called the Diabetes Physician Recognition
Program that recognizes physicians based on the quality of diabetes care
they provide using its diabetes measures Consumers can check online for a
listing of physicians who are recognized for the quality of the diabetes
care they provide More information about NCQA and its programs is
available at http://wwwncqaorg/

National Diabetes Quality Improvement Alliance

Organized by leading diabetes stakeholder groups in 1998, the Diabetes
Quality Improvement Project was a voluntary coalition of public and private
organizations that have cooperated to develop a national set of
diabetes-
specific performance and outcome measures In 2001, the DQIP partners
joined other leading organizations to form the National Diabetes Quality
Improvement Alliance The Alliance agreed to work on developing one
national performance measurement set for diabetes accepted by all major
stakeholders In October 2002, the newly formed Alliance developed
national, uniform consensus standards from purchaser, provider, and
consumer groups Further information is available on the Alliance Web site
at http://wwwnationaldiabetesallianceorg/
Incentives

Bridges to Excellence Project

Pay-for-performance initiatives have gained momentum in recent years as
health care analysts have recognized that a disincentive for quality
improvement exists in the US health care system because all providers
receive the same reimbursement regardless of the quality of their product
Leatherman, Berwick, Iles, et al, 2003 In its report, Crossing the
Quality Chasm, the IOM recommended that payments for care should be
redesigned to encourage providers to make positive changes to their care
processes Ideally, this shift will begin with purchasers and insurers and
filter down through the delivery system to
help encourage improvements at
all levels

In response to this challenge, a group of employers, physicians, health
plans and patients has come together to create Bridges to Excellence
focused on realigning incentives around higher quality The program has
created incentives through two programs, Diabetes Care Link and Physicians
Office Link The Diabetes Care Link requires certification or recognition
under NCQAs Diabetes Physician Recognition Program and then grants 1- or 3-
year recognition through a cash bonus system for participating physicians
delivering quality diabetes care The Diabetes Care Link program also
focuses on helping people with diabetes engage in their own care and
achieve better outcomes The program estimates a savings of 350 and a
cost of 175 per patient per year Bridges to Excellence, 2004 More
information on the Bridges to Excellence project is available at
http://wwwbridgestoexcellencecom/bte

JCAHO Codman Award

The Joint Commission on Accreditation of Healthcare Organizations is the
Nations leading accreditor of hospitals and other health care facilities
JCAHO has established the Ernest A Codman Award to recognize health care
organizations that use
process and outcomes measures to improve
organization performance and, ultimately, the quality of care provided to
the public The Codman Award was created in 1996 to showcase the effective
use of performance measures, and enhance knowledge and encourage the use of
performance measurement to improve the quality of health care Information
on this program is available at
http://wwwjcahoorg/accreditedorganizations/codmanaward/codman_overviewh
tm

Federal Programs and Resources for Diabetes Quality Improvement

In addition to public/private quality improvement efforts, State leaders
can also use Federal quality improvement programs and resources for State
efforts There are a variety of programs at the Federal level that address
diabetes and quality improvement, some of which are partnering with
States, and others that have useful resources for State efforts

Quality Interagency Coordination Task Force

In addition to preparing the first annual NHQR and subsequent reports, AHRQ
is also involved in diabetes care by overseeing the day-to-day operations
of the Federal Quality Interagency Coordination Task Force QuIC The
purpose of the QuIC is to ensure that all Federal agencies involved
in
purchasing, providing, studying, or regulating health care services are
working in a coordinated manner toward the common goal of improving quality
care This group has selected diabetes and depression as the first two
areas for which it will mount an effort to improve clinical quality of
care For diabetes, the work group is focusing its efforts on having all
Federal programs agree to use the DQIP measures of care and then to improve
health care provider performance based on these indicators More
information on this task force is available at http://wwwquicgov/

CDC Diabetes Prevention and Control Program

The Centers for Disease Control and Prevention currently funds the Diabetes
Prevention and Control Program in every State This program is discussed
extensively in Module 4: Action; for further information, see this section
of the Resource Guide

National Public Health Initiative on Diabetes and Womens Health

CDC, the American Diabetes Association, the American Public Health
Association APHA, and the Association of State and Territorial Health
Officials ASTHOcosponsor the National Public Health Initiative on
Diabetes and Womens Health Part of a comprehensive program to
improve
womens health, the CDC-lead initiative has three phases In Phase I, the
CDC prepared Diabetes Womens Health Across the Life Stages: A Public
Health Perspective Published in 2001, this report examined why diabetes is
a serious public health problem for women and analyzed the various factors
that affect diabetes in women This report also explored the impact of
diabetes on womens lives using the various life stages as a framework-
adolescence, reproductive years, middle age, and elder years A copy of
this publication is available on CDCs Web site at
http://wwwcdcgov/diabetes/projects/womenhtm

In 2001 during Phase II, CDC joined the ADA, APHA, and ASTHO to turn the
report into action The four groups convened a task force in November
2001, with representatives of over 40 organizations from the public,
private, and nonprofit sectors Proposed recommendations that emerged from
this meeting were published as the Interim Report: Proposed Recommendations
for Action and are also available on CDCs Web site at
http://wwwcdcgov/diabetes/pubs/interim/indexhtm In Phase III,
currently ongoing, multidisciplinary agencies-including government,
academic, voluntary, business,
community-based, and professional
organizations-selected recommendations of highest priority and identified
appropriate strategies for implementation This national agenda represents
the result of their deliberations for action Additional information is
available at http://wwwcdcgov/diabetes/pubs/action/indexhtm

Healthy People 2010

Healthy People 2010 is a national prevention program lead by the US
Department of Health and Human Services in partnership with other Federal
agencies, States, businesses, communities, and consumers HP2010 outlines
a broad range of objectives in health care with the goal of increasing the
quality and length of life and eliminating health disparities in the United
States Diabetes is one of the focus areas of HP2010

State leaders can use HP2010 objectives to assess health care quality
Some NHQR measures that relate to the HP2010 objectives still show room for
improvement Further information on HP2010 goals related to diabetes is
available at
http://wwwhealthypeoplegov/document/HTML/Volume1/05Diabeteshtm

HRSAs Health Disparities Collaboratives

HRSAs Bureau of Primary Heath Care and the CDCs Diabetes Prevention and
Control Program sponsor Health
Disparities Collaboratives, a unique
partnership with community health centers across the country aimed at
improving chronic illness care for underserved and minority communities
This program is discussed in Module 4: Action; for further information, see
this section of the Resource Guide

National Diabetes Program of the Indian Health Service

The National Diabetes Program of the Indian Health Service IHS is a
public health effort to improve the prevention and treatment of diabetes
among American Indian and Alaska Native populations This segment of the
US population suffers disproportionately from high rates of type 2
diabetes The IHS uses the following to track and improve diabetes care
quality among American Indian and Alaska Native populations:
Quality measures from the Indian Health Diabetes Care and Outcomes Audit,
which are similar to national DQIP measures
Case management to coordinate care and provide followup
Information management to identify patients and assure timely and
appropriate care
Practice teams to deliver multidisciplinary care and education
Systems of care that are clearly defined and close gaps in care
Patient education to assist patients
with managing their diabetes
Provider training to assure continuing education and competency
Protocol-based practice to ensure that evidence-based guidelines are
followed
Provision of specialty exams and services to ensure access to necessary
specialist services
Staging of populations to manage differing needs of various ages and
stages of disease progression

More information is available at
http://wwwihsgov/MedicalPrograms/Diabetes/indexasp

National Diabetes Education Program

The National Diabetes Education Program is a national collaboration
sponsored jointly by the NIH and the CDC This program is discussed in
Module 4: Action; for further information, see this section of the Resource
Guide

CMS Quality Improvement Organizations

Quality Improvement Organizations are designated as the guardians of
quality, cost-effective care for both Medicare and Medicaid This program
is discussed in Module 4: Action; for further information, see this section
of the Resource Guide

Appendix H: CDC Funding for States Diabetes Programs, 2003-2004

———————–
[1] This State-level analysis is feasible because of information collected
at the State level Similar
analyses may be possible for smaller
geographic areas within States For example, the HCUP data, described
below, permit analyses at the county or finer market areas Data related
to health care resource are generally available at the county level,
although data on health risk behaviors of the population generally are not
State analysts could use their county level databases to compare diabetes
quality measures based on HCUP data with other characteristics of counties
[2] Diabetes prevalence, poverty and obesity rates were selected because
they were most closely related to admissions for these avoidable
hospitalizations among a set of other factors studied including age of the
population, insurance coverage, and health resources
[3] HCUP Partners providing their data for this analysis were: Arizona
Department of Health Services, Colorado Health Hospital Association,
Georgia Hospital Association, Hawaii Health Information Corporation, Iowa
Hospital Association, Kentucky Department for Public Health, Maine Health
Data Organization, Massachusetts Division of Health Care Finance and
Policy, Michigan Health and Hospital Association, Missouri Hospital
Association, Texas Health Care
Information Council, Washington State
Department of Health, West Virginia Health Care Authority, Wisconsin
Department of Health and Family Services

———————–

The purpose of this Resource Guide on diabetes quality improvement is to:
Provide an overview of the factors that affect the quality of care for
diabetes
Present the core elements of health care quality improvement
Assist State policymakers and health care leaders in using the data from
the NHQR for planning State-level quality improvement initiatives
Provide a variety of best practices and policy approaches that national
organizations, the Federal Government, and States have implemented
related to diabetes quality improvement

Diabetes Facts

Description: Diabetes is a group of diseases characterized by the presence
of too much glucose in the blood In type 1 diabetes, the body does not
produce enough insulin In type 2 diabetes, the body may not produce
enough insulin or not use insulin properly Insulin is a hormone produced
by the pancreas to move glucose from the blood into the cells Glucose
also known more commonly as blood sugar provides energy for cells CDC,
2003b; American Diabetes
Association, 2003

Prevalence: 182 million people, 63 of the US population, are
estimated to have diabetes
13 million people are diagnosed; 52 million people do not know
they have diabetes CDC, 2003b

Cost: 132 billion total cost in 2002, making it the 6th most costly
medical condition
92 billion in direct medical costs, 40 billion in indirect costs
due to lost productivity and death
13,000 per year in average medical costs for individuals with
diabetes
2,500 per year for the average patient without diabetes Hogan, Dall,
Nikolov, 2003

Deaths: 213,062 estimated deaths, making it the Nations 6th leading
killer, although many experts believe the death rate from diabetes is
significantly underreported CDC, 2003c

Possible Complications:
Heart disease, hypertension, heart attacks and stroke
Digestive problems
Leg and foot ulcers and lower-limb amputation
Eye problems and blindness
Kidney disease and kidney failure
Coma and death
Other complications-susceptibility to infection; dental disease; skin
problems; sexual dysfunction; and increased risk for birth defects if

pregnant CDC, 2003c

AHRQs National Healthcare Quality Report
and National Healthcare Disparities Report

The NHQR, released in December 2003, is a call for all health care
professionals to consider ways to improve the quality of care in the United
States The report offers the first national consensus measures for
quality and the Federal Governments baseline for those measures The NHQR
chronicles the gap between actual medical practice and evidence-based
practice guidelines It addresses:

Objectives of high quality health care: effectiveness, safety,
timeliness, and patient centeredness IOM, 1999

The life-cycle spectrum of health care requirements: staying healthy,
getting better, living with illness or disability, and end-of-life care
IOM, 1999

Nine major priority areas: cancer, end stage renal disease, diabetes,
heart disease, HIV and AIDS, maternal and child health, mental health,
respiratory diseases, and nursing home and home health care

A total of 147 measures of specific good practice processes and
outcomes of care

The NHDR, also released in 2003, uses the same framework and measures to
report on health care quality by racial/ethnic and
socioeconomic groups
It also measures access to health care for these subgroups Although the
NHDR does not report by State, it provides national baselines of quality
and access measures for these vulnerable subgroups These are valuable
comparisons for how diverse populations are treated in a State

The NHQR can be found at:
http://wwwqualitytoolsahrqgov/qualityreport/download_reportaspx

The NHDR can be found at:
http://wwwqualitytoolsahrqgov/disparitiesreport/download_reportaspx

Figure I1
The Quality Improvement Process:
Links, Stages of Change, and Information Supports

DATA INFORMATION ACTION IMPROVEMENT

Measuring:

Methods
Measures
Background

Understanding Gaps
Opportunities:

Benchmarks
Customization
Making the case

Knowing
Improvement
Is Possible:

Success stories
Modeling
Trials

Implementing:

Program specifics
Operational solutions
Confirmation

Stages:

Supports:

Links:

Module Overview:
1 The Importance of Diabetes - Why should State leaders prioritize
diabetes?
a Rising prevalence
b Long-term complications
c High
costs
d Disparities in care
e Effectiveness of interventions
f Potential for return on investment
2 The NHQR and NHDR as Resources for State Leaders

a Gaps between recommended care and care received
b Variation in care across States
c Variation in care across population groups
3 The Quality Improvement Opportunity
4 Summary and Synthesis
5 Resources for Further Reading
6 List of Associated Appendixes for Use With This Module

Key Ideas in Module 1:

States have an established role and interest in preventing and
improving care for diabetes due to the complications associated with
diabetes as well as its costs, increasing prevalence, and problems
with disparities in care

Increasingly, research evidence points to the potential for cost
savings and improved quality of life from investments in improved
diabetes care quality

The National Healthcare Quality Report and National Healthcare
Disparities Report are new resources that State leaders can use to
assess diabetes care quality in their States and devise quality
improvement plans

What is
diabetes?

Diabetes is a group of diseases characterized by the presence of too much
glucose in the blood In type 1 diabetes, the body does not produce enough
insulin In type 2 diabetes, the body may not produce enough insulin or
not use insulin properly Insulin is a hormone produced by the pancreas to
move glucose from the blood into the cells Glucose also known more
commonly as blood sugar provides energy for cells

Type 1 diabetes usually begins in childhood and occurs when the cells that
produce insulin are destroyed; this type of diabetes accounts for 5 percent
to 10 percent of all diagnosed cases

Type 2 diabetes occurs as the body develops insulin resistance or the
pancreas loses the ability to produce insulin Type 2 diabetes is
associated with both genetic and behavioral factors including age, obesity,
physical inactivity, family history of diabetes, among other factors
Certain racial and ethnic groups are particularly at risk for diabetes,
including African American, Latino, American Indian, and Native Hawaiian
populations Normally seen in adults, type 2 diabetes is on the rise in
children and young adults This type of diabetes accounts for 90 percent
to 95 percent
of all diagnosed cases of diabetes

Gestational diabetes is caused by glucose intolerance that develops in some
women during pregnancy Women with gestational diabetes are at increased
risk of developing type 2 diabetes after pregnancy

People with the condition known as prediabetes have an increased risk of
developing diabetes Those with prediabetes have impaired fasting glucose
and/or impaired glucose tolerance The CDC estimates that as many as 41
million adults had prediabetes in 2000 Studies indicate that the
progression from prediabetes to diabetes is not inevitable People with
prediabetes can prevent or delay the onset of type 2 diabetes with weight
loss and increased physical activity

Once a person develops diabetes, there is currently no cure Diabetes must
be managed through proper treatment in order to avoid complications
Source: CDC National Diabetes Fact Sheet CDC, 2003b

Module Overview:

1 Quality Measurement
a Background
b Diabetes-Related Quality Measures in the NHQR
2 Sources of NHQR Data on Diabetes Care
a Process Measures-BRFSS and MEPS Data
b Outcome Measures-NHANES, HCUP, and NHDS Data
3
Filling Local Data Gaps
a Developing an Inventory of Local Data Sources
b Using Published Studies and Readily Available Data To Develop
State or Local Estimates
3 Summary and Synthesis
4 Resources for Further Reading
5 List of Associated Appendixes for Use With This Module

Key Ideas in Module 2:
Data are essential to quality improvement - essential for identifying
and measuring problems and setting goals for improvement The first
two steps are: 1 identifying measures and 2 identifying data
sources to support those measures

The NHQR is a valuable resource for consensus-based measures, national
and State-level data sources, and estimates for tracking diabetes care
quality

State leaders must understand the limitations of data sources to be
able to handle challenges who will say that the data are the problem,
not the health care system

States also have a wide array of other data sources Gaps in State-
level data can be filled by using methods from published national
studies and available State-level data, such as that collected or
analyzed by State
DPCP staff

Types of Quality Measures:

Process measures often are based on guidelines of care for a specific
condition Process measures are generally considered to be within the
control of the provider and, therefore, are considered performance
indicators They also are more likely to reveal actions that can be
taken to improve quality for example, whether a necessary test or
medication is given

Outcome measures generally are based on patient health status They are
considered to be the ultimate objective of quality improvement -
improving the patients health for example, mortality rates,
hospitalization rates, and test results

Structural measures reflect aspects of health care infrastructure that
generally are broad in scope, system wide, and difficult to link to
short-term quality improvement for example, the staff-to-bed ratio in a
hospital The NHQR does not use structural measures

Hospitalizations for long-term complications of diabetes per 100,000
population

Percent of adults receiving an HbA1c test in past year

Module Overview:
1 Deriving Information From Data
2 Step 1: Identifying Appropriate Metrics and
Comparisons
a Benchmark Metrics for States
b Understanding State Variation
c Four States Compared to Benchmarks
3 Step 2: Interpreting the Data: What Does It Mean?
a Factors That Affect the Quality of Diabetes Care
b Interpreting Process and Outcome Measures Together
4 Summary and Synthesis
5 List of Associated Appendixes for Use With This Module

Key Ideas in Module 3:

The need for information for understanding and planning is the reason
to assemble data on diabetes care

Analysis of the NHQR data tables can answer some key questions for
States:
o What measures should be used to set goals for quality diabetes
care?
Consensus-based measures with national endorsements
o What goals should be set as targets for specific measures?
Best-in-class estimates of achievable and practical levels
o What factors influence a States position among other States?
Health system factors, consumer behaviors, and immutable
population attributes

Process and outcome measures should be considered together to assess a
States diabetes care
quality

State-level baseline estimates of diabetes care allow States to assess
their starting point and to evaluate their progress over time

State-level baseline estimates across all conditions studied in the
NHQR afford State leaders a broad view of health care quality in their
State

All adults, except for flu vaccination which is for age 18 to 64

Source: Derived from the NHQR, 2003, based on CDC BRFSS

All adults, except for flu vaccination which is for age 18 to 64

Module Overview:
1 Selected Public/Private Quality Improvement Initiatives
2 Selected Federal Programs and Resources for Diabetes Care Quality
Improvement
3 State Approaches to Diabetes Care Quality Improvement
a Partnership/Planning
b Program Development
c Dissemination
d Profiles of Selected Best Practice States
4 Selected Local Quality Improvement Efforts
5 Summary and Synthesis
6 List of Associated Appendixes for Use With This Module

Key Ideas in Module 4:
There are a variety of quality
improvement initiatives at the
national, State, and local levels that are sparking change in health
systems across the Nation

States can use this module for examples and resources for action and
for assessing the scope of current diabetes quality improvement
efforts in a State

No comparative evaluation of State-level diabetes quality
improvement programs has been conducted; however, an evidence-based
systematic review of clinical efforts has found provider education,
disease management and use of multiple interventions most effective in
improving diabetes care

The Six Core Components of the Chronic Care Model

Community - Mobilizing all the available community resources to meet the
needs of people with chronic illnesses

Health System - Creating organizational cultures, systems and mechanisms
that promote safe, high quality care throughout the health care system

Self-Management Support - Empowering and preparing patients to manage
their health and navigate the health care system

Delivery System Design - Assuring the delivery of effective, efficient
clinical care and self-management support through
appropriate design of
the delivery system

Decision Support - Promoting appropriate clinical care consistent with
scientific evidence and patient preferences

Clinical Information Systems - Organizing patient and population data to
facilitate efficient and effective care for people with chronic
illnesses

Source: MacColl Institute for Healthcare Innovation, Group Health
Cooperative, 2004 The chronic care model: model elements ICIC is a
national program supported by the Robert Wood Johnson Foundation with
direction and technical assistance provided by Group Health Cooperatives
MacColl Institute for Healthcare Innovation

Types of Approaches to Organizing Diabetes Programs
States structure their public health programs differently Listed below
are samples of different ways that States have approached diabetes quality
improvement programs
Regional structures
Georgia provides diabetes services through its seven existing public
health districts
Pilot projects
Massachusetts worked in three pilot communities to enhance diabetes care
by integrating the health system with community diabetes development
Community-based grant support
New
Hampshire and South Carolina conduct many diabetes activities through
grants to community health centers or community organizations throughout
the State

Partnerships are key to everything we do - they are key to public health
The strength and commitment of our partners underlies our success

- Wisconsin Department of Health Official

The bottom line, no matter how you cut, is that its about relationships
and identifying what people bring to the table You look at your
objectives and those of other agencies or groups and see where it makes
sense to work together Then you help people to understand where the
synergy is by finding like goals
- Missouri Department of Health Official

The environment is so dynamic and things are changing so quickly -
science, policy, reimbursement We need some way to keep the finger on the
pulse and adjust quickly The Advisory Committee helps us do that

- Minnesota Department of Health Official

In setting up partnerships, think strategically about who might be a good
partner We sat down and thought about how people with diabetes get from A
to Z and who is involved in the process From there we identified all the
people, from individual
families to large health plans that could have an
influence on the process Then we invited input and involvement that would
represent all of those points of view
- California Department of Health Official

States are intimidated that there is so much they have to know We rely on
our partners to give us this knowledge You dont have to know everything
you just have to know the right people The environment may be changing,
but the experts arent
- Minnesota Department of Health Official

Dont get so bogged down in the details that you loose sight of the big
picture Diabetes is the quintessential chronic disease and you need to
look at the entire system of care Simply telling providers to work harder
and better will not work if the system is not structured to support them in
quality improvement
- California Department of Health Official

Getting the right people to share your message is the best thing you can
do to make sure people listen

- North Carolina Department of Health Official

It is vitally important that you include the people who are your target
audience in the planning of these programs
- California Department of Health Official

We feel strongly that if we want
them to partner, we need to be a partner
back This involves going to meetings they want us to be at and always
following through We take great care with our partners and always put
them out front to get credit for their efforts We want them to see how
important they are to this
- Wisconsin Department of Health Official

Simple lifestyle modifications such as healthy eating, moderate exercise,
and weight control have conclusively been shown to prevent Type 2 diabetes
by up to 60 percent These solutions are low-tech and low cost, and yet
they produce a high impact
- Dr Kimberlydawn Wisdom, Michigan Surgeon General

Michigan Diabetes Statistics

707,200 adults and 6,200 children are diagnosed with diabetes in
Michigan
Diabetes related medical care costs Michigan almost 6 billion per year
Sixty percent of direct costs were due to hospitalization
An additional cost of 35 billion is attributable to lost productivity
from premature death, disability, and illness
Much of the indirect cost was related to complications of blindness and
amputation

Module Overview:

1 A Model for Quality Improvement

a Plan-Do-Study-Act PDSA Model

b PDSA Case
Study: Wisconsin Collaborative Diabetes Quality
Improvement Project

2 Developing a State Strategy for Improving Diabetes Care Quality

3 Integrating Quality Improvement Activities Across Conditions

4 The Importance of Evaluation

5 Summary and Synthesis

6 Resources for Further Reading

Key Ideas in Module 5:

Although local contexts differ, standard quality improvement techniques
should be a part of any health care quality improvement strategy at the
State level

A variety of models can be used to inform State strategies to improve
health care This module focuses on the PDSA model adapted for the State
policymaking context

State leaders can use the adapted PDSA model and the tools in this module
to gather State-specific data, information, and action to produce a
quality improvement strategy suited to their locale

State leaders can integrate quality improvement efforts for diabetes with
other conditions or design more overarching quality improvement
strategies that target multiple health care conditions

W Edwards Deming popularized the Plan-Do-Check-Act model an idea of
Walter Shewhart, a statistician at the Bell
Telephone Laboratories and
focused manufacturers on the need to apply the model constantly to the
production process Deming is credited with General Douglas McArthur for
rebuilding Japan after World War II and setting the foundation for Japanese
production quality Tortorella, 1995

Being a member of the statewide diabetes collaborative project allowed our
plan to access materials, data, and people resources that would otherwise
have taken years to develop Being part of the collaborative group gave us
the means to send a coordinated, statewide message consistently and
coherently in a variety of formats

- Quality Management Specialist, Prevea Health Plan

Are there other quality improvement opportunities in my State in addition
to diabetes?

Each State should view its performance across the broad spectrum of quality
improvement measures, such as those contained in the NHQR The NHQR
contains data on many other chronic conditions that could be targets for
quality improvement initiatives Appendix F assembles all of the measures
from the NHQR that include State-level estimates

The models, processes, and tools for quality improvement in diabetes care
in this Resource Guide can be
applied to other disease areas that may also
be fruitful targets for quality improvement

Checklist of PDSA Quality Improvement Steps

Partner
V Establish or redesign an advisory board or steering committee to
identify areas of health care most in need of quality improvement in
the State The NHQR State-level data across all disease Appendix F
and the NHDR socioeconomic data might inform these deliberations
V Include the key experts and stakeholders in quality improvement,
including State DPCP officials and champions in health care who will
carry key messages to the front line of health care

Plan with Partners
V Decide on a set of questions or topic areas related to quality
improvement
V Develop an appraisal of how the State performs, why, and how the State
could improve
V Develop goals for quality improvement Some of the State-level
results described in the Module 4: Action, as well as NHQR data, might
inform the process
V Take an inventory of current diabetes quality improvement programs in
the State, including DPCP programming, and other local and
nongovernmental
initiatives Make a preliminary list of additional
actions to take See Table 52 above
V Identify data needs:
- Identify measures that address the topic, that have readily
available benchmarks, and that relate to action needed NHQR
data could inform this step
- Develop an inventory of potential data sources for the State or
locality that can address the topic and help analyze variation in
practice across the State This Resource Guide points to some
possible data sources for States in Module 2: Data and describes
approaches to analyzing data in Module 3: Information
- Determine whether special data collection must be undertaken and
how that can be accomplished
V Develop a preliminary evaluation plan to inform data collection needs

Do
V Assemble data
V Make initial estimates of measures agreed to by the Partners and
compare them to benchmarks Initial assessments may lead the
Committee to revise its original plan NHQR benchmarks should inform
this step
V Conduct or commission analyses to answer the questions raised in the
planning stage
and to develop information for deciding on actions to
be taken

Study
V Study the data and its implications for the quality improvement
strategy
V Prioritize areas for improvement
V Put together the case for taking action

Act
V Refine the action and evaluation plans with the Partners
V Find resources to develop and support the initiative
V Implement the action plan
V Implement the evaluation plan
V Assess whether improvement has occurred based on the evaluation data
V Make adjustments to the action plan as necessary and continue the
quality improvement process

Other Ideas for State Action to Improve Diabetes Care

For some State leaders, broad statewide quality improvement efforts may
seem unattainable or unrealistic, given the scope of their responsibilities
or the status of their budgets There are, however, other activities that
help raise awareness of quality improvement and build support over time for
larger diabetes quality improvement efforts Some options include the
following:

Talk with other organizations and individuals about ways to improve
diabetes care in your State eg, DPCP staff in the State
health
department, diabetes advocacy organizations, health care professional
organizations for diabetes, as well as providers and health plans
Convene a conference or advisory group of diabetes experts in the State
to discuss strategies for quality improvement or work with one that
already exists
Hold/participate in a legislative hearing or town-hall meeting on health
care quality in the State
Participate in State efforts to raise public awareness about obesity and
diabetes
Consider public-private partnerships and public-private collaboratives to
address diabetes quality improvement
Examine ways for State employee health programs, the State DPCP, and
Medicaid offices to work together to control diabetes and improve care
Help establish a disease management program for diabetes for State
employees or Medicaid clients by partnering with private sector
organizations for services

Diabetes prevalence
2002
20yo

Medicaid enrollment
1998

Medicaid
enrollment
2002

Medicaid population
by age
1998

Medicaid population
by race
1998

Diabetes prevalence
2002
60yo

Diabetes prevalence
by race
2002
20yo

Diabetes prevalence in the Medicaid population, 2002, 20-60yo and 60yo

Medicaid population
by race
1998
20-60yo and 60yo

Medicaid population
by race
2002
20-60yo and 60yo

Define age of population segment and assume proportion is the same across
race subgroups and apply to each
subgroup

Diabetes prevalence
by race
2002
20-60yo and 60yo

Apply diabetes prevalence by race and age, 2002, to the Medicaid
population, by race and age, 2002, and aggregate to Medicaid population

Calculate national diabetes prevalence
2002
20-60yo and 60yo

Apply proportion increase from 1998 to 2002 to each race subgroup for 1998,
20-60yo and 60yo

Assume age proportion is the same across race subgroups and apply
proportion to each subgroup

Per capita medical expenditures for people with diabetes, 2002

Medicaid spending for diabetes, 2002,
20yo

Original
Source
Data

Adjustments

Final Estimate

Final
Estimate

Benchmarks, Key Messages:

A benchmark:
Is a point for comparison
Is a place to start
May be inadequate or impractical from different vantage points

Methods matter:
They can have a large impact on comparisons

Healthy People 2010
Diabetes Care Topics
Education
New cases of diabetes
Overall cases diagnosed
Diagnosis
Diabetes deaths
Cardiovascular deaths
Gestational diabetes
Foot ulcers
Lower extremity amputations
Annual urinary microalbumin test
Annual glycosylated hemoglobin test
Annual dilated eye exams
Annual foot exams
Annual dental exams
Aspirin therapy
Self-blood-glucose-monitoring
Admissions uncontrolled diabetes

Legislative Options for Improving Diabetes Care

California SB 64 passed in 1999 mandated insurance coverage for diabetes
supplies and outpatient education including medical nutrition therapy

In 1996, Maines legislature passed Public Law 592 requiring all health
insurance policies
in Maine to cover ambulatory diabetes education and
followup programs

Recognizing the devastating effects of this disease without a
comprehensive approach to treatment, the Florida legislature passed
legislation in 1996 that requires all insurers to provide coverage for
all medically appropriate equipment and supplies in addition to diabetes
outpatient self-management training and educational services used to
treat diabetes

California AB 942, enacted in October 2003, allows non-licensed school
personnel to administer glucagon and also allows students with diabetes
to test their blood glucose levels in the classroom and self-manage their
disease anywhere on school grounds or at school sponsored events and
field trips

A number of States have passed authorizing legislation for Medicaid
disease management programs, many of them aimed at diabetes Examples of
recent State legislation include: Delaware 2003 House Joint Resolution
10; Illinois 2003 SB 0064; Iowa 2003 House File 619; New Mexico 2003 SB
0338; Texas 2003 HB 727 and 2003 HB 1735

Californias Diabetes Continuous Quality Improvement Project

In an effort to address problems
with undiagnosed diabetes and gaps in
quality for diabetes care, the California Cooperative Healthcare Reporting
Initiative CCHRI created the Diabetes Continuous Quality Improvement
Project Diabetes CQI The CCHRI is an alliance of purchasers, health
plans and providers in California that seek to improve health care quality
through collecting performance data, providing a forum for all sectors of
the health care industry to collaborate on quality improvement, and
disseminating information to a variety of audiences CCHRI is administered
by the Pacific Business Group on Health PBGH

A unique collaboration of purchasers, health plans, and providers,
Californias Diabetes CQI project seeks to:
Improve identification of diabetes
Improve data exchange between providers and health plans
Improve routine monitoring and testing of diabetes patients
Show measurable improvements in the health of diabetes patients
Develop a toolkit of interventions to help achieve project objectives
Evaluate the effectiveness of project interventions
Standardize clinical guidelines to create efficiencies across
providers
Promote information sharing and best
practices

Collaborators in the Diabetes CQI include the States largest employer
coalition, the Pacific Business Group on Health, as well as seven of
Californias largest health plans and 24 medical groups and independent
practice associations The California State DPCP is involved as a partner
in the project and has provided diabetes expertise as well as a public
health perspective to the business model being used by private sector
groups Collaborators have agreed on common treatment guidelines for
diabetes developed by DPCP and Diabetes Coalition of California that are
in agreement with ADA clinical practice recommendations and a common
toolkit of interventions, eliminating confusion and conflicting information
from different sources

Different parts of the projects overall objectives are accomplished
through several programs:
The Quality Improvement, Learning and Teaching program QUILT
provides support to provider groups that are fostering population-
based practice improvements Site visits and initial assessments,
monthly teleconferences, quarterly meetings and individualized
consultation help advance quality improvements in clinical settings

The Clinical Benchmarking Study collects data on the quality of care
provided to people with diabetes by the 24 provider organizations
Provider organizations and employers can use the information to track
improvements in care over time, improve disease management
interventions, and identify and disseminate best practices
The project developed a common Intervention Toolkit for providers that
includes patient and provider education materials, medical chart
inserts and checklists, and other tools to improve clinical care
quality More than 300 tools were evaluated for a variety of clinical
criteria and then evaluated for ease of use The project arrived at 40
reliable resources that it included in the Intervention Toolkit,
distributed it to plans and providers, and provided training on how to
use it

More information on the Diabetes CQI is available at
http://wwwdiabetescqiorg/about/indexasp

All adults, except for flu vaccination which is for age 18 to 64

Table D2 National averages for diabetes care measures, available in the
NHDR by race/ethnicity and
income

Rate

Percent of adults with

diabetes who had a

hemoglobin A1c

measurement at least

once in the past year

MEPS

898

911

860

857

868

888

901

914

TBD/59

BRFSS

2000

Percent of patients with

diabetes who had a lipid

profile in past two years

MEPS

943

946

948

912

867

940

941

n/a

Percent of adults with

diabetes who had a

retinal eye examination in

past year MEPS

665

678

658

583

634

644

609

745

75/47

NHIS

2000

Percent of adults with

diabetes who had a foot

examination in past year

MEPS

664

679

604

662

603

682

654

687

75/55

BRFSS

1998

Percent of adults with

diabetes who had an

influenza immunization in

past year MEPS

548

592

434

466

481

576

513

587

n/a

Hospital admissions for

uncontrolled

uncomplicated diabetes

per 100,000 population

HCUP

269

167

836

416

699

427

296

158

54/72

HCUP

1996

Hospital
admissions for

short-term complications

of diabetes per 100,000

population HCUP

481

388

1291

402

967

681

536

339

n/a

Hospital admissions for

long term complications

of diabetes per 100,000

population HCUP

1174

881

2910

1762

2358

1581

1279

869

n/a

Hospital admissions for

lower extremity

amputations in patients

with diabetes per 1,000

population NHDS

n/a

18/41

NHDS

1997

Total and racial/ethnic estimates are from MEPS or HCUP, expect the last
measure which is from NHDS

Income group values for HCUP and BRFSS are based on median income of the
patients ZIP Code

Source: National Healthcare Disparities Report, 2003

Black Non-

Hispanic

Negative or poor

MEPS

Measure

National

consensus-

based goal

HP2010,

Target/

Baseline

Poor or low MEPS

25k-35k HCUP

Middle MEPS

35k-45k HCUP

High MEPS

45k HCUP

National Total

All races/

ethnicities

Racial/ethnic group average

Income group average

White

Diabetes-Related Quality Measures in the NHQR

The NHQR uses two kinds of data measures for
diabetes care quality: process
and outcome measures These measures are discussed in Module 2: Data and
Appendix C

Process Measures - based on guidelines for care for a specific condition
The NHQR uses five diabetes process measures:
HbA1c test: Percent of adults with diabetes who had a hemoglobin A1c
measurement HbA1c at least once in the past year
Lipid profile: Percent of patients with diabetes who had a lipid profile
in the past two years
Eye exam: Percent of adults with diabetes who had a retinal eye
examination in the past year
Foot exam: Percent of adults with diabetes who had a foot examination in
the past year
Flu vaccination: Percent of adults with diabetes who had an influenza
immunization in the past year

Outcome Measures - based on patient health status The NHQR uses two types
of outcome measures for diabetes-test results and avoidable
hospitalizations-as follows:
Test Results:
o HbA1c levels: Percent of adults with diagnosed diabetes with HbA1c
levels 95 percent poor control; 90 percent needs
improvement; and 70 percent optimal control
o Cholesterol levels: Percent of adults with diagnosed diabetes with

most recent LDL-C level 130 mg/dL needs improvement; 100
optimal
o Blood pressure: Percent of adults with diagnosed diabetes with
most recent blood pressure 140/90 mm/Hg
Avoidable Hospitalizations:
o Hospital admissions for adults with Lab?ËÞåòóõö G H J
L W X ?
ôàÏàôÄ?z?ôÄm?Ä?ShÎiËh
|ùOJ[4]QJ[5]J[6]h
|ùhJÑOJ[7]QJ[8]J[9]h
|ùh
|ùOJ[10]QJ[11]J[12]hÎiËhJÑ6?OJ[13]QJ[14]J[15]h
|ùOJ[16]QJ[17]J[18]hLhJÑOJ[19]QJ[20]J[21]hJÑOJ[22]QJ[23]J[24]hÎiËhJÑ
OJ[25]QJ[26]J[27]hÎiËhJÑ5?OJ[28]QJ[29]J[30]h
|ù5?OJ[31]QJ[32]J[33] hJÑ5?CJ0OJ[34]QJ[35]\?J[36]aJ0h
uncomplicated, uncontrolled diabetes per 100,000 population
o Hospital admissions for adults with short-term complications of
diabetes per 100,000 population
o Hospital admissions for adults with long-term complications of
diabetes per 100,000 population
o Hospital admissions for lower extremity amputations for patients of
all ages with diabetes per 1,000 population

Source:hispanichealth.com

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