Abstract: To date, evidence on pay-for-performance has been mixed. When pay-for-performance policies improve health outcomes, researchers should evaluate whether these health gains are worth the incremental costs (financial incentives and increased utilization) needed to achieve them. We used simulation modeling to evaluate the cost-effectiveness of two pay-for-performance policies that were recently evaluated in major journals: 1) a randomized controlled trial of financial incentives on patients, physicians, or both for cholesterol control (Asch et al. JAMA 2015); and 2) a retrospective cross-country analysis of the United Kingdom’s Quality and Outcomes Framework, the world’s largest primary care pay-for-performance program (Ryan et al. Lancet 2016). We worked with the authors of these studies to estimate the cost-effectiveness of these programs and to identify the key drivers (e.g., levels of health effects, levels of incentive payments, or modeling assumptions) of our model-based results.
Ankur Pandya, MPH, PhD, is an Assistant Professor of Health Decision Science in the Department of Health Policy and Management at the Harvard T.H. Chan School of Public Health.