Regression Discontinuity Design to Evaluate of Drotrecogin Alpha Effectiveness

Many health care interventions and medications found to have benefits ("efficacy") in experimental, tightly-controlled, human research trials are later found to lack real-world health benefits ("effectiveness"). Inadequate surveillance of real-world clinical effectiveness may falsely reassure clinicians and those who monitor healthcare quality, propagating unrecognized ineffective or harmful treatments at high costs to patients and society. The failure to translate potential health benefits into realized gains, or to detect unexpected harms in healthcare delivery, stems from a lack of methods with which to robustly measure real-world (in)effectiveness. Current methods to detect changes in outcomes 'before and after' implementation may be biased by secular trends in healthcare practice and outcomes; other methods to compare outcomes for treated and untreated patients may be biased by unmeasured factors. The current project aims to develop and demonstrate - as a proof-of-concept - the use of a quasi-experimental research method called 'regression discontinuity design (RDD)' in surveillance of real-world clinical effectiveness. RDD had previously found use in the evaluation of educational programs in which students scoring below a threshold were assigned an intervention. The US Department of Education considers RDD designs to have quality similar to randomized trials.