The Lack of Screening for Diabetic Nephropathy: Evidence from a Privately Insured Population

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1 115 The Lack of Screening for Diabetic Nephropathy: Evidence from a Privately Insured Population Arch G. Mainous III, PhD; James M. Gill, MD, MPH Background: We examined the performance of screening tests for diabetic nephropathy in a population of privately insured individuals. Methods: Administrative data from a large private health plan were analyzed. Continuously insured persons with diabetes (ages 30 62) with > one office visit during the study year (July 1995 to June 1996) were included (n=4,758). Outcome variables included a urinalysis for protein and a test for microalbuminuria. The likelihood of test performance according to age, gender, insurance plan type, total office visits, diabetes office visits, and specialty of predominant physician was examined both in bivariate analyses and a logistic regression. Results: Among the 4,623 patients without evidence of nephropathy, only 16.5% had a urinalysis test conducted sometime in the year. All individuals (2.1% of sample) who received a microalbuminuria test also received a urinalysis. Individuals with indemnity or PPO plans were more likely to be screened than individuals in point-of-service plans. Patients with more visits and more diabetes visits were more likely to be screened. In the regression with family practice as the reference category, general internists were the only physician specialty more likely to have screened patients. Conclusions: The majority of patients with diabetes mellitus do not receive annual screening for microalbuminuria or urinary protein. (Fam Med 2001;33(2):115-9.) Type 2 diabetes mellitus is a common chronic disease that has frequent but potentially preventable complications. High-quality medical care can lead to better control of diabetes and ultimately to a reduction in the rate of these complications. 1 There is widespread agreement that specific tests are necessary to monitor for early signs of diabetic complications. 2 Diabetic nephropathy is a frequent complication of diabetes mellitus, leading to increased morbidity and mortality, an impaired quality of life, and a high financial burden for the health care system. 3,4 The presence of microalbuminuria is strongly predictive of future development of end-stage renal failure. 5 Consequently, the American Diabetes Association (ADA) recommends an annual urinalysis for protein and an annual microalbumin measurement if the urinalysis is negative for protein. 1,2 From the Department of Family Medicine, Medical University of South Carolina (Dr Mainous); and the Department of Family and Community Medicine, Christiana Care Health System (Dr Gill), Wilmington, Del. Since primary care physicians, rather than diabetes specialists, provide the majority of care to persons with diabetes mellitus, it is important to gain an understanding of the quality of care provided in both primary care and specialty settings. 4 Although past studies like the analysis by Weiner et al 6 have investigated the quality of care provided to patients with diabetes, these studies are limited in their implications. First, the studies have focused on elderly Medicare populations but have not examined the privately insured populations that make up a significant proportion of persons with diabetes. Second, they have examined monitoring for hyperglycemia, hyperlipidemia, and retinopathy but have generally not examined screening for nephropathy. Since screening for nephropathy is now recommended by the ADA and other groups, it is important to examine the extent to which persons with diabetes receive this screening. In a survey of primary care physicians in Indiana regarding self-reported screening for microalbuminuria and overt albuminuria, 82% of physicians reported screening more than half of their type 2 diabetes patients

2 116 February 2001 Family Medicine annually for overt albuminuria. 7 Realizing that selfreports of physicians about their quality of care may be affected by a desire to provide a response indicating high-quality care, this study examined, with administrative data, the performance of urine protein and microalbuminuria tests in a population of privately insured individuals with diabetes. Methods Design and Population This study was a cross-sectional analysis of administrative claims data. We included persons with diabetes mellitus in a large private insurance plan in the Mid- Atlantic region (Pennsylvania, New Jersey, and Delaware). One of the largest, both regionally and nationally, this health plan has approximately 3 million individuals enrolled in the Mid-Atlantic region and nearly 15 million enrolled in the United States. Diabetes was defined by the presence in claims data of at least two separate diagnoses of diabetes (defined by an International Classification of Diseases, Ninth Edition [ICD- 9] code of 250.xx) during the study year. Two diagnoses were required to minimize overcounting persons with rule-out diagnoses; this methodology has been used in previous studies. 8 We selected a 100% sample of persons with diabetes who were continuously insured over the 1-year period to (allowing for up to 45 days of disenrollment) and who were ages as of The age requirements allowed us to focus on adult diabetics who did not have Medicare insurance. This population selection methodology is in accordance with guidelines of the Health Plan Employer Data and Information Set (HEDIS). 9 We included persons who made at least one physician office or clinic visit during the study year. This was necessary to identify the predominant physician and to allow the physician an opportunity to order appropriate tests. Office visits were defined by presence of claims with the following Current Procedural Terminology, Fourth Edition (CPT-4) codes: , , , , , , or We excluded visits to nonphysician providers, such as podiatrists, chiropractors, and optometrists, since these providers usually do not provide general medical care for diabetes and would not be expected to undertake screening for proteinuria. We also excluded nurse practitioners and other nonphysician providers, who comprised less then.01% of office visits. This method of including only physician office visits is consistent with previous similar studies. 6,8 Finally, we included patients who were enrolled in any of three health plan types: indemnity, preferred provider organizations (PPOs), or point-of-service (POS); we excluded patients in prepaid health maintenance organization (HMO) plans because our claims data did not fully capture services for persons in these plans. Although it is unfortunate that the prepaid HMO group was unable to be included, the included groups (not prepaid HMO) actually represent the fastest-growing types of health insurance. 10 The final population included 4,758 patients. Variables Urinalysis for protein was determined by the presence of claims with the following CPT codes: 81000, 81001, 81002, 81003, and A test for microalbuminuria was determined by the presence of claims with the codes and Presence of diabetic nephropathy was operationalized according to the HEDIS 2000 criteria. If an individual s record had one of the following codes, that individual was labeled as having nephropathy: CPT codes: 8100, 81001, 81002, 81003, 36800, 36810, 36815, 50300, 50340, 50360, 50365, 50370, 50380, 90920, 90921, 90924, 90925, 90935, 90937, 90945, 90947, 90989, 90993, 90997, and International Classification of Diseases, Ninth Edition (ICD-9-CM) codes: 39.27, 39.42, 39.43, 39.53, 39.93, 39.94, 39.95, 54.98, 55.4, 55.6, 250.4, 403, 404, , , , , 753.0, 753.1, 791.0, V42.0, V45.1, and V56. DRG codes: 316 and 317. The specialty of the patient s predominant physician was examined in relation to screening for nephropathy. The predominant physician was defined as the one the patient visited most during the year, as defined in previous studies. 11 The specialty of each physician was determined by the insurance provider files and categorized into family physician, general practitioner, general internist, endocrinologist, other specialist, or unknown. When a patient made the same number of visits to two or more physicians, we considered the predominant physician the one who was more primary care oriented (family physician or general practitioner, then general internist, then endocrinologist, then other specialist, then unknown). Analysis Plan The rate of performance of screening tests among patients without demonstrated nephropathy was computed. We also computed the rate of tests among patients with demonstrated nephropathy. Chi-square analysis and t tests were used to examine the likelihood of test performance according to age, gender, insurance plan type (indemnity, POS, PPO), total office visits, office visits where primary diagnosis is for diabetes (250.xx), and specialty of predominant physician. Finally, we computed a logistic regression model; the dependent variable was receipt of urinalysis sometime during the year or not, and the independent variables were age, number of office visits in the year, gender (male was the reference category), insurance plan type (idemnity/ppo was the reference category), and physician specialty (family practice was the reference category).

3 117 Table 1 Demographic Characteristics of Diabetic Population Without Nephropathy* Mean age (years + SD) Gender Males 2,593 (56.1%) Females 2,030 (43.9%) Insurance plan Indemnity/preferred provider organization 1,726 (37.3%) Point of service 2,897 (62.7%) Mean total visits in study year (+ SD) Mean diabetes visits in study year (+ SD) Specialty of predominant physician General practice 466 (10.1%) Family practice 1,566 (33.9%) Internal medicine 1,912 (41.4%) Endocrinology 340 (7.4%) Other 160 (3.5%) Unknown 179 (3.9%) * n=4,623 SD standard deviation Results The analysis yielded 4,623 individuals with diabetes without evidence of nephropathy. Their demographic characteristics are shown in Table 1. The majority of these patients were ages 45 and older, male, and in POS health plans. More than 85% had a generalist physician as their predominant physician, while 7.4% predominantly saw an endocrinologist. Among persons with no evidence of nephropathy, 761 (16.5%) had a urinalysis test conducted in the year. All individuals (n=97) who received a microalbuminuria test also received a urinalysis. Thus, 2.1% of those without nephropathy received a test for microalbuminuria during the study year. Of individuals with evidence of nephropathy (n=135), 29 (21.5%) had a urinalysis test conducted in the year. As with the individuals without nephropathy, all individuals with nephropathy (n=7) who received a microalbuminuria test also received a urinalysis. Thus, 5.2% of those with nephropathy received a test for microalbuminuria during the study year. Table 2 indicates the relationship between performance of either a urinalysis or microalbuminuria test among individuals without nephropathy and potential differentiating factors. Individuals with indemnity or PPO plans were more likely than individuals in POS plans to be screened. Patients with more visits and more diabetes visits were more likely to be screened. Finally, individuals whose predominant provider was an endocrinologist were more likely to have received the test. There was no significant difference in mean age between those screened ( ) and those not screened ( , P=.10). However, individuals who were screened had more visits ( ) than those who weren t screened ( , P=.0001). Similarly, individuals who were screened had more visits for diabetes ( ) than those who weren t screened ( , P=.001). Table 3 indicates the results of the logistic regression. Patients were more likely to be screened if they had more office visits, were younger, and if they received their care in a indemnity/ppo plan. Compared to patients of family physicians, patients of general internists were more likely to get screened. However, after controlling for other potentially confounding variables, patients of endocrinologists were not more likely than patients of family physicians to get screened. Discussion The results of this study indicate that in a population of privately insured patients with diabetes, the use of screening tests for nephropathy are suboptimal and not in line with either past or recent recommendations proposed by the ADA. 12,13 The rates of screening for urine protein were very low, and screening for microalbuminuria was nearly nonexistent (2%). Tests for microalbuminuria are not given to patients instead of urinalysis for proteinuria but rather in addition to urinalysis. Individuals with more visits and more visits for diabetes were more likely to have been screened for urine protein. Further, individuals whose predominant phy- Table 2 Relationship Between Performance of Screening Test and Characteristics of Diabetic Population Without Nephropathy* % Screened P Value Gender.096 Males 15.8 Females 17.3 Insurance plan.001 Indemnity/preferred provider organization 19.8 Point of service 14.5 Specialty of predominant physician.023 General practice 15.9 Family practice 14.1 Internal medicine 17.8 Endocrinology 19.4 Other 18.1 * n=4,623

4 118 February 2001 Family Medicine sician was an endocrinologist were more likely to have received a test. This suggests that the likelihood of receiving appropriate monitoring tests may be related to increased encounters with the health care system, when diabetes is the primary agenda for the visit. It may be worthwhile to examine how diabetes management can be integrated into primary care in a more structured way to capitalize on the apparent benefits of visits focused specifically on diabetes. A strategy that may have particular success is based not on opportunistically performing tests in the context of acute visits but rather is based on the mini-clinic diabetes management model that is used in the United Kingdom. 14 Mini-clinics are blocks of practice time devoted to the care of patients with a specific chronic disease. Mini-clinics have been linked to improved glycemic control and reduced hospitalizations. 14,15 Several reasons may account for why the majority of patients are not receiving care consistent with ADA guidelines. First, the data we used for this analysis were from a time period in which the ADA s recommendations were to have an initial screen using a urine protein test and, if it was negative, to then perform a test for microalbuminuria. This may account for why tests for microalbuminuria are lower than might be expected with current guidelines suggesting screening for microalbuminuria. However, even using the context of urinalysis as the general quality standard in the time period, only 16.5% of the patients received a test for gross proteinuria in the year. Second, some physicians may agree that although microalbuminuria is a marker for increased morbidity and mortality in patients with Table 3 Results of Logistic Regression of Factors Related to Performance of Urinary Protein Screening Test Factor 95% CI Odds Ratio Gender (Male is reference) Insurance plan (Indemnity/Preferred Provider Organization is reference) Specialty of predominant physician (Family physician is reference) General practice Internal medicine Endocrinology Other Age Office visits CI confidence interval diabetes, they may also feel that the current level of evidence does not indicate that following the screening guidelines improves patient outcomes. A third reason is that patients may have the tests recommended by their physician but may be unable or unwilling to have the test performed. The present results of a baseline analysis of patientlevel administrative data indicate that there is substantial room for improvement in the use of monitoring tests for individuals with diabetes. The results are also in contrast to self-reports of primary care physicians, which would suggest that these tests for nephropathy are performed significantly more often than the rate found here. 7 Several reasons may explain this difference. First, physician self-report of socially desirable (ie, high-quality) behaviors may be biased by respondents estimating their behavior to be more in line with quality standards than objective counts would substantiate. Consequently, physicians may say or even believe that their behavior is more in line with quality standards than it really is. Second, since we were focusing on patient-level care, a comparison to physician behavior may not be completely comparable because patients may not have continuity with the doctor and seek care from several locations or providers. However, when we examined the likelihood of receiving the tests according to the predominant specialty of the physician, it was clear that the rate of tests among patients with a predominant provider of any specialty was still low, compared with physician self-report. Limitations Several potential limitations should be considered in interpreting the results of this study. Most important are the inherent limitations in using claims data. While claims data are an efficient data source for examining use across large populations, they are not always accurate indicators of clinical information, such as procedures and diagnoses. For example, it could be that some urinalyses were not captured in claims data because they were done during an office visit, and the physician did not submit a separate claim for the test. As with other self-report data, the physician had to accurately record the information, ranging from the diagnosis to specialty. It could be argued that failure to obtain urinalyses is not a significant problem, since most patients should have also had a microalbumin test, which is much more likely to be captured in claims data. In fact, the most recent ADA guideline recommends that all persons with diabetes receive an annual microalbumin test. 12 While the guidelines that were effective during the study period did allow for use of urinalysis as an initial screen, they also stated that persons with a negative urinalysis should receive a microalbumin test. 13 Presumably, most

5 119 persons with a positive urinalysis would also have had a follow-up microalbumin test or had been classified as having diabetic nephropathy (and therefore would have been excluded from the main analysis). We are studying only specific aspects of diabetesspecific care (ie, likelihood of receiving tests for diabetic nephropathy). While we measured performance against widely known and accepted guidelines for diabetes care, it could be argued whether the tests we measured are appropriate for every patient or whether other tests might also be good indicators of quality. Also, while our population is large and encompasses three states, we did not include states outside of the Mid- Atlantic region. Neither did we include elderly patients or those with public insurance, HMO insurance, or no insurance. Finally, failure to check for proteinuria may be of little significance, because a recent article suggested that a more cost-effective strategy in a population of patients with diabetes was to give all middle-aged patients ACE inhibitors rather than screening for microalbuminuria. 16 It is possible that some physicians may have adopted this strategy in the time frame we investigated, thereby decreasing the likelihood of screening tests since the patients were already being treated for nephropathy. We could not assess medication use of our study population. Conclusions The rate of screening tests for nephropathy among diabetic patients is suboptimal and has substantial room for improvement. Future research should focus on initiatives to improve detection of nephropathy in patients with diabetes. REFERENCES 1. American Diabetes Association. Standards of medical care for patients with diabetes mellitus. Diabetes Care 1997;20:S5-S American Diabetes Association. Clinical practice recommendations, Diabetes Care 1999;22:S1-S Piehlmeier W, Renner R, Schramm W, et al. Screening of diabetic patients for microalbuminuria in primary care: the PROSIT Project. Exp Clin Endocrinol Diabetes 1999;107: Nelson RG, Knowler WC, Pettitt DJ, Bennett PH. Kidney diseases in diabetes. In: National Diabetes Data Group, eds. Diabetes in America, second edition. NIH publication no Bethesda, Md: National Institutes of Health, 1995: McKenna K, Thompson C. Microalbuminuria: a marker to increased renal and cardiovascular risk in diabetes mellitus. Scott Med J 1997;42: Weiner JP, Parente ST, Garnick DW, Fowles J, Lawthers AG, Palmer RH. Variation in office-based quality. A claims-based profile of care provided to Medicare patients with diabetes. JAMA 1995;273: Kraft SK, Lazaridis EN, Qiu C, Clark CM Jr, Marrero DG. Screening and treatment of diabetic nephropathy by primary care physicians. J Gen Intern Med 1999;14: O Connor PJ, Desai J, Rush WA, Cherney LM, Solberg LI, Bishop DB. Is having a regular provider of diabetes care related to intensity of care and glycemic control? J Fam Pract 1998;47: HEDIS 3.0, Health plan employer data and information set. Washington, DC: National Committee for Quality Assurance, Marquis MS, Long SH. Trends in managed care and managed competition, Health Aff 1999;18: Rosenblatt RA, Hart LG, Baldwin LM, Chan L, Schneeweiss R. The generalist role of specialty physicians: is there a hidden system of primary care? JAMA 1998;279: American Diabetes Association. Standards of medical care for patients with diabetes mellitus. Diabetes Care 2000;23:S32-S American Diabetes Association. Standards of medical care for patients with diabetes mellitus. Diabetes Care 1994;17: Farmer A, Coulter A. Organization of care for diabetic patients in general practice: influence on hospital admissions. Br J Gen Pract 1990;40: Koperski M. How effective is systematic care of diabetic patients? A study in one general practice. Br J Gen Pract 1992;42: Golan L, Birkmeyer JD, Welch HG. The cost-effectiveness of treating all patients with type 2 diabetes with angiotensin-converting enzyme inhibitors. Ann Intern Med 1999;131: Acknowledgments: This study was supported in part by a grant from LifeScan, Inc. Corresponding Author: Address correspondence to Dr Mainous, Medical University of South Carolina, Department of Family Medicine, PO Box , 295 Calhoun Street, Charleston, SC Fax: mainouag@musc.edu.