Background: Disease Management Programmes (DMPs) are proposed to enhance the quality of care, to improve health outcomes and to reduce costs. Yet, the evidence regarding the effectiveness of such structured approaches remains uncertain. Randomized controlled trials (RCTs) represent the gold standard of evaluation for complex interventions. However, most of the evidence derives from non-randomized or even uncontrolled trials. We therefore tried to assess the impact of a randomized control group on the interpretation of DMP effectiveness.
Methods: We analyzed the data of a RCT on a DMP for diabetes type 2 by creating two scenarios. The first solely includes data of the intervention group (n=649), representing an 'uncontrolled pre-test-post-test analysis'. The second comprehends all data (n=1489) of the 'randomized controlled analysis'. HbA1c was used as the primary outcome measure for metabolic control in diabetes. Depending on either scenario, we calculated relative and absolute risk reduction regarding clinically relevant endpoints and estimated costs by extrapolating our results according to the UK Prospective Diabetes Study (UKPDS) findings.
Results: The HbA1c reduction attributed to the DMP was 0.41% (uncontrolled analysis) vs. 0.13% (controlled comparison). Estimations of relative risk reduction for cardiovascular disease were 4.6% vs. 1.4%. The estimated numbers needed to treat (NNT) to avoid one myocardial infarction within 10 years differed from 125 (uncontrolled analysis) to 417 patients (controlled comparison), which led to a substantial scenario-dependent difference in cost estimations.
Conclusion: Uncontrolled pre-test-post-test evaluation might lead to crucial overestimation of DMP effectiveness. We therefore recommend randomized controlled evaluations prior to long-term implementation.