Characterizing Rational Transplant Program Response to Outcome-Based Regulation.

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. Organ transplantation is an increasingly common therapy for many types of end-stage organ failure, including lungs, hearts, kidneys, and livers. The last 20 years have seen increased scrutiny of posttransplant outcomes in the United States to ensure the efficient utilization of the scarce organ supply. Under regulations by the Organ Procurement Transplantation Network (OPTN) and Centers for Medicare and Medicaid Services (CMS), the United States has seen a rise in risk-averse patient selection among transplant programs, resulting in decreased transplantation volume for some programs. Despite this observed decrease, the response of transplant programs to OPTN/CMS regulations remains poorly understood. In this work, we consider the perspective of a transplant program that seeks to simultaneously maximize transplant volume and control the risk of OPTN/CMS penalization. Using a chance-constrained mixed-integer programming model, we demonstrate that under certain conditions, it may be rational for a transplant program to curtail its transplant volume to avoid penalization under OPTN/CMS regulations. This finding, which confirms empirical results observed in the clinical literature, suggests that such regulations may be inherently unsuitable for use in incentivizing improved program performance. We also highlight other structural shortcomings of OPTN/CMS regulations that have not been observed previously in the literature. Funding: This work was supported by the U.S. Department of Defense and the National Science Foundation [Grants CMMI-1826144, CMMI-1826297, and CMMI-1826323]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/opre.2018.0721. [ABSTRACT FROM AUTHOR]