Optimal quality oversight in kidney transplantation and its impact on transplant centers’ waitlist management

Zahra Gharibi (), Hung T. Do (), Michael Hahsler () and Mehmet U. S. Ayvaci ()
Additional contact information
Zahra Gharibi: California State University San Marcos
Hung T. Do: University of Vermont
Michael Hahsler: Southern Methodist University
Mehmet U. S. Ayvaci: University of Texas at Dallas

Health Care Management Science, 2025, vol. 28, issue 3, No 3, 410 pages

Abstract: Abstract This paper studies the effects of quality oversight in the context of assessing kidney transplantation-related outcomes and possible unintended consequences (e.g., cherry-picking of organs and selection of healthier transplant candidates). In this context, we propose a stochastic economic model that identifies socially optimal kidney transplant choices given the inherent trade-off between the expected wait time and the quality of the received donor kidney for a given patient. Socially optimal decisions seek to maximize the utilitarian welfare function defined as the sum of all patients’ post-transplant expected utilities. To determine the social loss, we compare the socially optimal decisions to those taken by a transplant program that maximizes its utility. We derive the optimal quality oversight policy that minimizes social loss and examine how decisions are impacted due to the changes introduced by the new Kidney Allocation System. Our empirical analysis using data from the Scientific Registry of Transplant Recipients and United States Renal Data System indicates that current quality oversight imposed through Conditions of Participation results in inefficient transplant decisions for 56% of recipients, and the performance is inconsistent across different regions and parameters. We propose that the risk-adjusted post-transplant performance assessment policy considers the factors impacting demand-supply parameters such as organ availability in the 11 US transplant regions, candidates’ blood type, and the newly introduced Kidney Allocation System. Policymakers and providers can utilize insights from our findings to design effective oversight mechanisms and make informed decisions regarding transplant and waitlist management that yield desired outcomes.

Keywords: Kidney transplantation; Quality oversight; Queuing model in healthcare; Stochastic model; New kidney allocation system; Operations research; Operations management (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10729-025-09713-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:kap:hcarem:v:28:y:2025:i:3:d:10.1007_s10729-025-09713-x

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10729

DOI: 10.1007/s10729-025-09713-x

Access Statistics for this article

Health Care Management Science is currently edited by Yasar Ozcan

More articles in Health Care Management Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().