Patients with Type 2 Diabetes Benefit from Primary Care-Based Disease Management: A Propensity Score Matched Survival Time Analysis

Abstract

This study aimed to assess the impact of a nationwide German diabetes mellitus disease management program (DMP) on survival time and costs in comparison to routine care. The authors conducted a retrospective observational cohort study using routine administration data from Germany's largest sickness fund to identify insured suffering from diabetes in 2002. A total of 95,443 insured with type 2 diabetes mellitus who were born before January 1, 1962 met the defined inclusion criteria, resulting in 19,888 pairs of DMP participants and nonparticipants matched for socioeconomic and health status using propensity score matching methods. This is the first time propensity score matching has been used to evaluate a survival benefit of DMPs. In the time frame analyzed (3 years), mean survival time for the DMP group was 1045 days vs. 985 days for the routine care group (P<0.001). Mean daily hospital and total costs (including DMP administration and medical costs) were lower for the DMP group in the case of deceased insureds (92€ vs. 139€ and 122€ vs. 169€, respectively) as well as for censored observations (6€ vs. 7€ and 12.9€ vs. 13.4€, respectively). Mean daily drug costs were slightly lower for deceased insured in the DMP group (difference 0.6€), while no identifiable difference was found for censored observations. In this study, insured who were enrolled in a DMP for diabetes mellitus in the German Statutory Health Insurance showed a significant benefit in survival time. They also incurred lower costs compared to propensity score matched insured in routine care.

Economic Impact of Integrated Care Models for Patients with Chronic Diseases: A Systematic Review

“…All the included studies were prone to bias because of methodological decisions. Most of the articles [25][26][27][28][29][30][31][32][33][34][35][36][37][38] reported the results of nonrandomized studies, which resulted in potential selection bias. In addition, the methodological information was often difficult to find and therefore many questions concerning bias remained unanswered.…”

Selective enrollment in Disease Management Programs for coronary heart disease in Germany – An analysis based on cross-sectional survey and administrative claims data

“…To overcome the assumed selection bias, many studies analyzing the effectiveness of DMPs apply propensity score matching [5, 7–10]. Yet, those studies often use routinely collected administrative claims data only, and thus, some factors potentially influencing DMP enrollment cannot be included.…”

The Comparison of Matching Methods Using Different Measures of Balance: Benefits and Risks Exemplified within a Study to Evaluate the Effects of German Disease Management Programs on Long‐Term Outcomes of Patients with Type 2 Diabetes

“…; Drabik et al. ). All studies have applied matching techniques, either using direct covariate (Miksch et al.…”

“…; Drabik et al. ). PSM was always used with a 1:1 matching ratio, a logistic regression model to estimate the PS and covariate balance checks using standardized mean differences.…”

“…; Drabik et al. ) with some authors suggesting that using PSM is superior to previous approaches (Linder et al. ; Drabik et al.…”