Objectives: To assess the differentiated effects of population-based disease management programs (DMPs) for type 2 diabetes on intermediary clinical outcomes in The Netherlands.
Methods: Data covering a period from 20 to 24 months between January 2008 and December 2010 were collected from 18 Dutch care groups (primary care provider networks that have bundled payment contracts for delivery of diabetes DMPs). Meta-analysis and meta-regression methods were used to conduct differentiated analyses of these programs' effects over time on 4 clinical indicators: glycated hemoglobin, lowdensity lipoprotein, systolic blood pressure, and body mass index. Heterogeneous average results were stratified according to various patient and process characteristics to investigate whether differences in these features could explain variation in outcomes.
Results: Between 56% and 71% of patients (N = 105,056) had valid first- and second-year measurements of the study outcomes. Although average changes in these measures over time were small, stratified analyses demonstrated that clinically relevant improvements were achieved in patients with poor first-year health values. Interactions with age, disease duration, comorbidity, and smoking status were not consistent across outcomes; nonetheless, heterogeneity in results decreased considerably when simultaneously correcting for known patient characteristics. Positive effects tended to diminish with longer length of follow-up, while greater measurement frequency was associated with improved results, especially in patients with poor health.
Conclusions: Our data suggest that tailored disease management, in which not only evidencebased guidelines but also patient characteristics directly determine care processes, including self-management support, has great potential to improve the cost-effectiveness of current chronic care delivery.