Characterizing Rational Transplant Program Response to Outcome-Based Regulation

Abstract

U.S. health agencies periodically evaluate transplant programs based on their patients’ posttransplant survival outcomes, and a program is flagged for review if the number of unsuccessful transplants far exceeds what would be expected based on national averages. Some researchers have expressed concerns that these regulations might cause programs to reject high-risk patients, whereas others have questioned if such a response would be rational. In “Characterizing Rational Transplant Program Response to Outcome-Based Regulation,” Mildebrath et al. use chance-constrained optimization to demonstrate that it may, in fact, be rational for a transplant program to become more selective when evaluating transplant candidates for admittance to the waitlist. They also demonstrate that the regulations may unfairly penalize medium-sized programs. Moreover, their model quantifies which patients may be most at risk for adverse selection by programs. Their results provide insights to policymakers by quantitatively characterizing the response of rational programs to outcome-based regulations.