Disease management programs in type 2 diabetes: quality of care.

OBJECTIVES: To determine whether disease management programs (DMPs) for type 2 diabetes mellitus (T2DM) can improve some processes of care and intermediate outcomes. STUDY DESIGN: Two cross-sectional registries of patients with T2DM were used for data extraction before (previous cohort) and after (recent cohort) introduction of DMPs in Germany (N = 78,110). METHODS: In the recent cohort, 15,293 patients were treated within the DMPs and 9791 were not. Processes of care, medications, and intermediate outcomes (achievement of treatment targets for low-density lipoprotein [LDL] cholesterol, blood pressure, and glycosylated hemoglobin [A1C]) were analyzed using multi- variable, multilevel logistic regression, adjusting for patient case-mix and physician-level clustering to derive odds ratios and 95% confidence intervals (CIs). RESULTS: Availability of structured diabetes education and of lipid, blood pressure, and A1C measurements increased over time. In DMP patients, availability was significantly higher for blood pressure and A1C but not for lipid measurements. Prescription of angiotensin-converting enzyme inhibitors, oral antidiabetic drugs, and insulin increased over time and was more common in DMP patients. Statin prescription increased over time but was not influenced by DMP status. Intermediate outcomes improved over time, but DMPs had no influence on intermediate outcomes except for reaching LDL cholesterol targets (odds ratio 1.12 [95% CI 1.06, 1.19] in favor of DMPs). CONCLUSIONS: While there may be some unmeasured confounding, our data suggest that improvement in processes of care by DMPs, as implemented in Germany, only partially translates into improvement of intermediate outcomes.

Patterns and predictors of statin prescription in patients with type 2 diabetes.

BACKGROUND: The benefit of statins for prevention of cardiovascular events in type 2 diabetes is established, but a gap exists between guideline recommendations and clinical practice. The aim of the study was to identify patient-related factors predicting statin prescription. METHODS: We assessed the quality of care in 51,640 patients with type 2 diabetes in a German diabetes registry. Patients were stratified according to primary and secondary prevention. Five-year risk for cardiovascular events was calculated in primary prevention patients. A multivariate adjusted logistic regression model was constructed to determine which parameters influenced statin prescription. RESULTS: 34% had established atherosclerotic disease and 25.5% received a statin. Prescription was significantly higher in the secondary compared to the primary prevention group (38.1% [95% CI 37.4-38.9%] vs. 18.5% [95% CI 18.0-19.0%], respectively). In primary prevention the odds for statin prescription increased with estimated cardiovascular risk (OR 1.17 per 5% increase in 5-year risk, 95% CI 1.11-1.22). Positive predictors for statin prescription were secondary prevention, hypertension, former smoking, baseline LDL-cholesterol, and microalbuminuria. The odds of receiving a statin had an inverted U-shaped relation with age (nadir, 66 years), age at first diagnosis of diabetes (nadir, 56 years), and body mass index (nadir, 32 kg/m2). The model predicted prescription in 70% of the patients correctly. CONCLUSION: The majority of patients with type 2 diabetes are not receiving statins. The predominant factors determining statin prescription are the patient's prevention status and, in primary prevention, estimated cardiovascular risk. The results suggest that although physicians are aware of the general concept of cardiovascular risk, they fail to consistently implement guidelines.