the potential national cost-savings generated for those with diabetes and hiv/Aids. For example, if a diabetes. patient is hospitalized with disease-related …
Quality of Preventive Care for Diabetes: Effects of Visit Frequency and Competing Demands
Joshua J Fenton, MD, MPH1 Michael Von Korff, ScD2 Elizabeth HB Lin, MD, MPH2 Paul Ciechanowski, MD, MPH3 Bessie A Young, MD, MPH4
1
ABSTRACT
PURPOSE We sought to determine the association between timely receipt of diabetes-related preventive services and the longitudinal pattern of outpatient service use as characterized by a novel taxonomy that prioritized visits based on the Oregon State Prioritized Health Services List METHODS We performed a cross-sectional analysis of mail survey and automated
Department of Family and Community Medicine, University of California, Davis, Sacramento, Calif
2
Center for Health Studies, Group Health Cooperative, Seattle, Wash
3
Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, Wash
4
health care data for a population-based sample of patients with diabetes enrolled in a health maintenance organization in Washington State N 4,463 Outcomes included American Diabetes Associationrecommended preventive services, including regular hemoglobin A1C HbA1C monitoring, retinal examination, and microalbuminuria screening Patients
with fewer than 8 visits during the 2-year study period were considered infrequent users, while patients with 8 or more visits were classified as lower-priority users if most visits were for conditions of relatively low rank on the Oregon list and as higher-priority users otherwise
RESULTS After adjustment for social, demographic, and clinical factors, and depres-
Department of Medicine, University of Washington, and Veterans Administration Hospital, Seattle, Wash
sion, infrequent users had significantly reduced odds of receiving at least 1 HbA1C test odds ratio [OR] 035, 95 confidence interval [CI], 024-051, retinal examination OR 074, 95 CI, 063-086, and microalbuminuria screening OR 075, 95 CI, 058-096 relative to higher-priority users during the previous year Lower-priority users also had relatively reduced odds of receiving at least 1 HbA1C test OR 059, 95 CI, 035-101, retinal examination OR 068, 95 CI, 056-084, and microalbuminuria screening OR 079, 95 CI, 057-109 despite attending a similar mean number of total visits as higher-priority users
CONCLUSIONS Patients who attend relatively few outpatient visits or who attend
more frequent visits for predominantly
lower-priority conditions are more likely to receive substandard preventive care for diabetes
Ann Fam Med 2006;4:32-39 DOI: 101370/afm421
INTRODUCTION
egular medical care can prevent many common diabetes complications, including ischemic heart disease, stroke, retinopathy, nephropathy, and neuropathy1 The American Diabetes Association ADA recommends that persons with diabetes receive at least semiannual hemoglobin A1C HbA1C monitoring, annual retinal examination to monitor or screen for retinopathy, and annual microalbuminuria testing to screen for nephropathy2 The delivery of ADA-recommended services has been estimated to require 2 to 4 annual medical visits for most patients with diabetes2 Despite the effectiveness of preventive care for diabetes, many patients do not receive recommended services3 One contributing factor may be that some patients simply do not make regular clinic visits for diabetes care, and patients who receive infrequent outpatient monitoring may be
R
Conflicts of interest: none reported
CORRESPONDING AUTHOR
Joshua J Fenton, MD, MPH Department of Family and Community Medicine University of California, Davis 4860 Y St, ACC 2300 Sacramento, CA 95817
joshuafenton@ucdmcucdavisedu
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less likely to receive recommended preventive services4,5 Additionally, many patients with diabetes have comorbid chronic illness, and the exigencies of managing comorbid conditions may distract clinicians from the delivery of recommended preventive services6-8 Moreover, acute illnesses account for the majority of primary care visits, and clinicians are much less likely to perform tasks that may facilitate prevention during acute illness visits9 Thus, longitudinally, both the quantity and content of outpatient care may affect the delivery of timely preventive services for diabetes In this study, we used a novel taxonomy of outpatient visits to characterize the pattern of outpatient service use among a population-based sample of patients with diabetes The taxonomy classified patients by the quantity of outpatient visits over a 2-year period, the types of services received eg, acute vs chronic illness, and the relative effectiveness of the services received, with more effective services
designated higher priority and less effective services, lower priority From the perspective of the health system, we then framed 2 hypotheses related to the delivery of diabetes-related preventive services First, we hypothesized that patients who infrequently attended outpatient visits would be at increased risk for deferred diabetes-related preventive services, because clinicians may have insufficient opportunity to recommend preventive services to these patients Second, we hypothesized that patients with diabetes who frequently sought care for lower-priority conditions would be less likely to receive timely diabetes-related preventive services, because patient demand for relatively lower-priority services may compete for clinicians time and attention during office visits, thereby reducing the likelihood of preventive service delivery We focused on the competing demand for lower-priority medical care, because health systems would ideally devote limited resources to care of proven effectiveness with the greatest potential societal health benefit If many patients receive care for lower-priority conditions instead of recommended preventive services, interventions may be needed to
ensure the delivery of effective preventive services among many patients who may preferentially seek care for such conditions
of depression among adult patients with diabetes who were identified from a validated centralized diabetes registry that includes enrollees based on antidiabetic drug prescriptions, laboratory abnormalities, and outpatient and inpatient diagnostic codes11 The survey response rate was 617, including 4,463 subjects who responded to a depression screen and provided informed consent for linkage to automated clinical and pharmacy data Within GHC, diabetes care is generally provided by office-based primary care clinicians Although clinicians have access to electronic diabetes flow sheets populated with registry data, no general policies dictate how individual practices use the registry, and there are no formal systems in place to remind patients that diabetes preventive services are due The institutional review boards of GHC and the University of Washington approved the study protocol Patterns of Outpatient Use We characterized patients pattern of outpatient service use with a newly developed taxonomy of outpatient visits that relies on International
Classification of Diseases, Ninth Revision ICD-9 diagnostic codes, which GHC clinicians identify after outpatient encounters To develop the taxonomy, we categorized each ICD-9 code resulting from an adult outpatient visit in 2002 into 1 of 7 major diagnostic categories: acute diseases, chronic diseases, symptoms and ill-defined conditions, mental illnesses, vision and hearing disorders, dermatologic diseases, and preventive care and pregnancyrelated conditions We defined chronic diseases as conditions that typically last for more than 3 months, are recurrent, or have a chronic course in one quarter or more of incident cases Symptoms and ill-defined conditions included most ICD-9 diagnoses from codes 780 to 799 but also some chronic symptomatic conditions that have uncertain pathophysiology or lack objective diagnostic signs or therapies of proven effectiveness eg, irritable bowel syndrome We subsequently used the Oregon State Prioritized Health Services List12 to subclassify acute and chronic diseases into higher-priority diseases those for which medical care provides proven or likely benefit and lower-priority diseases those for which medical care provides lesser benefit in terms
of morbidity, mortality, or quality of life Using an evidence-based methodology, commissioners for the Oregon Health Plan created the prioritized list of more than 700 diagnosis and treatment pairs to assist in defining the benefits of Medicaid expansion13 To prioritize acute and chronic diseases, we mapped ICD-9 diagnoses in these diagnostic categories to corresponding diagnoses on the prioritized list If the diagnosis ranked 350 or greater on the list, we classified the disease as higher prior
METHODS
Design, Setting, and Patients We performed a population-based, cross-sectional study of adult enrollees with diabetes within Group Health Cooperative GHC, a staff-model health maintenance organization serving approximately 450,000 persons in western Washington State The methods of sampling have been previously described10 In 2001, a mail survey was conducted to estimate the prevalence
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ity; otherwise, we preliminarily classified the disease as lower priority Three coauthors JJF, MVK, EHL independently reviewed each diagnosis
that mapped to diseases of intermediate rank on the Oregon list codes 351-549 and decided by consensus to reclassify a substantial number of diseases as higher priority eg, acute sinusitis To assess coding reliability, another clinician blinded to the initial classification results recoded the diagnostic category of the 279 most common acute, chronic, or ill-defined condition diagnoses, and the priority of the 142 most common diagnoses that fell in the intermediate-priority range on the Oregon list The clinicians coding of diagnostic category and priority agreed with that of the 3-coauthor committee for 814 and 803 of diagnoses, respectively, and agreement for both was 753 We used automated health care data to identify all outpatient visits made by patients during the 2-year period surrounding their survey dates We categorized each visit by its major diagnostic category using its associated ICD-9 codes When a visit had more than 1 ICD-9 code, we weighted each by the reciprocal of the total number of codes We then generated counts of outpatient visits within each diagnostic category for patients during the study period Our goal was to identify patients who used relatively few
outpatient services and, among more frequent users, to distinguish patients seeking care for predominantly higher-priority acute and chronic diseases from those who received a preponderance of care for lower-priority acute and chronic diseases, and symptomatic conditions We therefore categorized patients based on their overall frequency of acute, chronic, and symptomatic illness visits and the relative priority of conditions addressed during these visits We excluded visits for mental illnesses, vision and hearing disorders, and preventive care and pregnancy-related conditions because they were less relevant to characterizing patients care for acute and chronic illness We also excluded visits for dermatologic conditions, because the most common diagnostic codes within this category were nonspecific and difficult to prioritize When a visit included diagnoses within excluded categories along with acute, chronic, and symptomatic illness diagnoses, we counted only the visit fraction associated with the latter diagnoses After examining the distribution of acute, chronic, and symptomatic visits, we set a threshold for infrequent visits of these types of 8 in a 2-year period We classified
patients with fewer than 8 visits as infrequent users Among patients with 8 or more visits, we classified patients as lower-priority users if one half or more of their visits were for lower-priority diagnoses or ill-defined conditions, and as higher-priority users if
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less than one half of their visits were for lower-priority diagnoses or ill-defined conditions Use of Diabetes-Related Preventive Services We used automated administrative and laboratory data for patients during the 2 years before survey completion to measure the receipt of ADA-recommended preventive services2 We examined 2 outcomes related to monitoring for glycemic control in the previous year: 1 receipt of at least 1 HbA1C test and 2 receipt of at least 3 HbA1C tests among patients with poor glycemic control ie, those whose most recent HbA1C value was 80 Two outcomes reflected timely monitoring for diabetic retinopathy: 1 at least 1 screening retinal examination in the previous year and 2 at least 2 retinal examinations in the 2 previous years among patients known to have retinopathy ie, annual surveillance Finally, among patients who had not been prescribed an angiotensin-converting
enzyme ACE inhibitor before the survey 419, we determined whether each received microalbuminuria screening during the previous year Social, Demographic, and Clinical Covariates The mail survey elicited information for social and demographic covariates education, marital status, and race and height and weight to compute body mass index Each patient also completed the Patient Health Questionnaire-9, a validated screening instrument that provides dichotomous diagnoses of major and minor depression14 We used automated diagnostic data to identify 7 complications of diabetes retinopathy, nephropathy, neuropathy, cerebrovascular disease, cardiovascular disease, peripheral vascular disease, and ketoacidosis15 and automated laboratory data to obtain the HbA1C result nearest the survey date We used pharmacy data to identify prescriptions for oral hypoglycemic medications and insulin as an indicator of treatment intensity and to compute an index of chronic disease comorbidity an RxRisk score, which is as predictive of future health care costs as ambulatory care groups16 We excluded medications for diabetes and depression when computing the index to avert duplicate measurement of these
diagnoses Analyses We performed bivariate comparisons of characteristics of infrequent, lower-priority, and higher-priority users, followed by 2 tests to determine the association between use pattern and preventive service outcomes We then used logistic regression analysis to test the hypothesis that infrequent and lower-priority users would be less likely to receive timely preventive ser
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vices after adjusting for potentially confounding factors identified in bivariate analyses The reference group in these models was higher-priority users, and each model included age, sex, marital status, education, chronic disease comorbidity quartile of RxRisk scores, number of diabetes complications, treatment intensity, depression status none, minor, and major, and primary care clinic We selected these covariates because each was significantly associated with use pattern in bivariate analyses and would plausibly affect delivery of preventive services In subsequent adjusted analyses, we found that smoking and body mass index had no substantive effect on study
results and so did not include them in final models Analyses of survey nonresponse bias have been previously described in detail10 In brief, nonrespondents
were younger, were more likely to be using insulin, and had higher HbA1C values, and had a higher prevalence of heart disease To judge whether nonresponse bias affected our results, we repeated the analyses with observations weighted by the inverse of the predicted probability of response propensity score17 Because there were only trivial differences in weighted and unweighted analyses, we report the unweighted analyses here We used 2-sided hypothesis tests and an of 05
RESULTS
Sample Characteristics The patients had a mean age of 65 years and a broad range of diabetes treatment intensities and complications Table 1 About 1 in 5 patients were nonwhite,
Table 1 Social, Demographic, and Clinical Characteristics of Patients by Pattern of Use of Outpatient Services
Pattern of Use Characteristic
Women, No High school education or less, No Marital status, No Single Married/living as Widowed Divorced or separated Nonwhite race, No Age, y, mean SD RxRisk comorbidity score, No 1,300 1,300-2,599 2,600-4,399 4,400 Diabetes
complications, No 0 1 2 3 HbA1C 80, No Treatment intensity, No None or diet Oral hypoglycemic agent Insulin oral hypoglycemic BMI 30 kg/m2, No Smoking currently, No Depression status, No Not depressed Minor depression Major depression
HbA1c hemoglobin A1c; BMI body mass index Infrequent users were 353 of the total sample; lower-priority users, 121; and higher-priority users, 525 Sample size may vary because of missing data All comparisons across use patterns are statistically significant P 001, except for the comparison for race P 28
Total Sample N 4,463
2,175 487 1,088 247 431 100 2,925 660 547 124 526 118 892 204 649 126 915 205 1,147 257 1,178 264 1,223 274 1,404 314 1,405 315 853 191 801 179 1,982 463 1,134 254 1,986 445 1,343 301 2,147 488 381 86 3,552 795 375 84 536 120
Infrequent n 1,576 663 421 345 221 177 113 1,077 688 132 84 179 114 334 374 601 127 527 334 506 321 387 246 156 99 774 491 549 348 187 119 66 42 682 465 462 293 790 501 324 206 727 468 184 118 1,344 853 108 69 124 79
Lower-Priority n 542 321 592 115 214 48 89 348 646 72 134 71 132 111 124 615 137 118 218 145 268 157 290 122 225 183 338 199 367 112 207 48 89 197 380 188 347 252 465 102 188 308
580 44 83 410 757 47 87 85 157
Higher-Priority n 2,345 1,191 501 628 271 206 89 1,500 645 343 148 276 119 447 501 658 132 270 115 496 212 634 270 945 403 447 191 657 280 554 236 687 293 1,103 482 484 206 944 403 917 391 1,112 482 153 67 1,798 767 220 94 327 139
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Table 2 Outpatient Visits During the 2-Year Study Period by Pattern of Use
Pattern of Use Type of Visit
Acute disease–higher priority Acute disease–lower priority Chronic disease–higher priority Chronic disease–lower priority Symptoms and ill-defined conditions Total
Total Sample N 4,463
19 27 13 18 75 74 13 19 16 24 136 112
Infrequent n 1,576 05 08 05 08 30 16 03 06 04 07 48 20
Lower-Priority n 542 19 19 32 27 48 31 31 28 42 42 173 94
Higher-Priority n 2,345 28 32 14 16 112 84 15 19 18 20 187 115
Values are mean SD numbers of visits Excludes visits for dermatologic diagnoses, vision and hearing, mental health illness, and preventive and pregnancy-related services All comparisons across use patterns are statistically significant P 001
and 12 had
major depression More than one third 35 were infrequent users, whereas 1 in 8 12 were lower-priority users and more than one half 52 were higher-priority users Infrequent users were younger and predominantly male, and they had less chronic disease comorbidity, fewer diabetes complications, and a lower prevalence of depression than lower- or higher-priority users Table 1 Lower-priority users were predominantly female, were more likely to be treated by diet alone, and had intermediate levels of chronic disease and a higher prevalence of major depression Higher-priority users tended to be older and to have less education and higher rates of diabetes complications and chronic disease comorbidity
Lower- and higher-priority users had a similar mean number of visits during the study period; however, higher-priority users made more than twice as many visits for higher-priority chronic diseases Table 2 During the 2-year study period, infrequent users had a mean of fewer than 5 visits, of which approximately 3 were for higher-priority chronic diseases Receipt of Preventive Services Higher-priority users consistently had the highest rates of timely preventive services for diabetes, whereas
lower-priority users typically had rates that were intermediate between those of higher-priority and infrequent users Figure 1 Among patients with poorly
Figure 1 Receipt of diabetes preventive services by patterns of use
Higher-priority 1 HbA1C n 4,463
Lower-priority
Infrequent
3 HbA1C if HbA1C 8 n 2,086
1 retinal examination n 4,463
2 retinal examinations in prior 2 years if known retinopathy n 1,206
Microalbuminuria screening n 1,873
0
HbA1C hemoblogin A1C
20
40
60
80
100
Note: Values are rates of receipt of services over a 2-year period Microalbuminuria screening was assessed only in patients who did not have a prescription for an angiotension-converting enzyme inhibitor at baseline Comparison of outcomes across use patterns are statistically significant P 001, except for the comparison of microalbuminuria screening P 05
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controlled diabetes HbA1C values 80, the majority 549 of higher-priority users had received 3 or more HbA1C tests in the previous year, whereas rates of regular HbA1C
monitoring were significantly lower among lower-priority users 444 and infrequent users 295 P 001 With regard to screening for diabetic retinopathy, higher-priority users had a significantly higher rate of timely screening during the previous year 676, whereas the screening rate was comparable among lower-priority users 541 and infrequent users 562 P 001 A similar pattern was seen among patients with known retinopathy, for whom annual surveillance examination is recommended Finally, higher-priority users were the most likely and infrequent users were the least likely to have received microalbuminuria screening during the previous year P 05 After adjustment for potentially confounding social, demographic, and clinical factors, a pattern of lower-priority or infrequent use remained associated with reduced odds of receiving timely HbA1C monitoring, screening or surveillance retinal examinations, and microalbuminuria screening Table 3 Relative to higher-priority users, infrequent users had significantly reduced odds across each preventive service outcome Lower-priority users had significantly reduced odds of timely retinal screening or surveillance relative to higher-priority users
and consistent but nonsignificant trends toward reduced odds of timely HbA1C monitoring and microalbuminuria screening
DISCUSSION
We found that patients who made infrequent visits were least likely to receive timely diabetes-related preventive care We also found that patients who made frequent visits for lower-priority health conditions were
at increased risk for delayed diabetes-related preventive services despite making a number of total visits comparable to that of a group that typically received care for higher-priority conditions Our findings are therefore consistent with our hypotheses that patterns of infrequent or lower-priority outpatient use would be associated with lower-quality diabetes preventive care Infrequent users were at the highest relative risk for not receiving recommended preventive services Similarly, patients with diabetes who had 2 or fewer annual visits to suburban Los Angeles primary care practices were less likely to receive timely proteinuria and lipid testing, although this analysis did not account for specialty clinic visits4 Patients with diabetes treated by diet alone are less likely to receive timely HbA1C testing, microalbuminuria testing, or
retinal screening,5 which may be attributable to less frequent clinic visits among patients managed in this way18 Infrequent users in our sample made a mean of 3 higher-priority chronic disease visits during the 2-year study, while lower-priority users made approximately 5 Currently, more than one third of US patients with diabetes visit their physicians less than quarterly18 Given the complexity of diabetes management, it may be difficult to deliver high-quality diabetes care during 2 or 3 annual office encounters Office systems that facilitate patient follow-up, opportunistic prevention, and guideline adherence might improve rates of diabetes preventive care among subpopulations of infrequent users, such as younger men with less comorbidity11 Lower-priority users were frequent users of outpatient services but had a preponderance of visits for lower-priority or ill-defined conditions During outpatient visits, physicians must resolve the tension between multiple competing demands, which may include the evaluation of patient complaints, chronic illness care, or preventive and counseling services19 When patients have acute symptoms, primary care physicians are much
Table 3 Adjusted
Odds of Timely Receipt of Diabetes-Related Preventive Services by Pattern of Use
Pattern of Use Diabetes-Related Preventive Service
1 HbA1C test in previous year n 4,347 3 HbA1C tests in previous year if HbA1C 8 n 1,837 1 retinal examinations in previous year n 4,347 2 retinal examinations in 2 previous years if known retinopathy n 1,179 1 microalbuminuria screenings in previous year n 1,831 Infrequent OR 95 CI 035 024-051 044 035-056 074 063-086 057 040-081 075 058-096 Lower-Priority OR 95 CI 059 035-101 080 057-112 068 056-084 055 034-089 079 057-109 Higher-Priority OR 95 CI ref ref ref ref ref
OR odds ratio; CI confidence interval; HbA1C hemoglobin A1C; ref reference group Includes fewer patients than bivariate analyses because of missing data Odds ratios adjusted for age, sex, marital status, ethnicity, education, comorbidity RxRisk score, number of diabetes complications, treatment intensity, depression status, and clinic site Among patients not prescribed an angiotensin-converting enzyme inhibitor
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less likely deliver preventive or counseling services or to engage in activities that would facilitate receipt of preventive care20,21 Lower-priority users may be less likely to receive preventive services if patient concerns about acute or chronic symptoms divert clinicians attention from the delivery of preventive services for diabetes Although studies suggest that competing demands affect depression management22 and cancer screening,7,8 we are unaware of previous research examining the impact of competing demands on diabetes care Primary care clinicians should be aware that patients with diabetes who frequently seek care for lower-priority conditions are at risk for deferred preventive care for diabetes, and health systems might consider interventions to promote effective preventive services among chronically ill patients who frequently seek care for lower-priority conditions Group visits among adults with chronic illness, for example, are associated with improved quality of care, clinical outcomes, and patient satisfaction, while reducing medical costs23,24 The limitations of our study deserve consideration First, based on diagnostic codes, our visit taxonomy may be prone to
misclassification, and patients within each of the 3 use categories may have had different numbers of total visits We believe, nevertheless, that our method of categorization provides a meaningful characterization of patients longitudinal pattern of outpatient service use that may be useful to health planners Second, we can only indirectly infer from diagnostic data that patient demand, rather than a clinician decision, stimulated the delivery of care for lowerpriority conditions Investigators have consistently observed, however, that patient requests powerfully influence the content of primary care visits,20,21,25,26 and we believe it is unlikely that clinicians, in the absence of patient demand, would so commonly prioritize care for lower-priority conditions over diabetes care among a substantial fraction 12 of this population-based sample Finally, we studied an insured population within a single health maintenance organization in the Pacific Northwest The findings may not be generalizable to other populations with diabetes The strengths of our study include its large, population-based sample and our ability to control for a broad range of important covariates, including
demographic and socioeconomic factors, diabetes complications, treatment intensity, chronic disease comorbidity, and depression status Additionally, access to clinical and administrative databases for a closed population allowed us to create comprehensive accounts of patients outpatient use during the study period, including both primary and specialty care, and to ascertain preventive service outcomes with a high degree of confidence Enrolled in a prepaid health plan, patients
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had universal access to assigned primary care clinicians, minimizing confounding related to health care access We found that a pattern of infrequent use was a robust risk factor for failing to receive recommended preventive services for diabetes, and patients with frequent outpatient use for predominantly lower-priority diagnoses were at increased risk for deferred preventive services for diabetes Although many of the health care needs of patients with chronic illness can be anticipated and planned, office practice remains organized principally to respond to patients acute complaints27 Innovations in the organization of primary care may be needed to ensure the delivery of
evidence-based services in the context of sparse patient demand or demand for care for conditions that are relatively less amenable to effective medical intervention
To read or post commentaries in response to this article, see it online at http://wwwannfammedorg/cgi/content/full/4/1/32 Key words: Chronic disease; disease management; preventive health services; diabetes; health services research; patient compliance; delivery of health care Submitted May 12, 2005; submitted, revised, August 24, 2005; accepted September 15, 2005 Funding support: This work was supported by National Institute of Mental Health grants MH-41739 and MH-01643 Dr Wayne J Katon, Principal Investigator and American Cancer Society Mentored Research Scholar grant MRSGT-05-214-01-CPPB to Dr Fenton Dr Fenton was a Robert Wood Johnson Clinical Scholar during early phases of this project Disclaimer: The statements herein are the authors and do not necessarily represent the views of the Robert Wood Johnson Foundation Acknowledgment: The authors thank Wayne Katon, Malia Oliver, Greg Simon, and other members of the Pathways study team for their assistance with this research
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