A novel two-stage network data envelopment analysis model for kidney allocation problem under medical and logistical uncertainty: a real case study.

Autor: Hamidzadeh F; School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran. farhad.hamidzadeh@gmail.com., Pishvaee MS; School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran. pishvaee@iust.ac.ir., Zarrinpoor N; Department of Industrial Engineering, Shiraz University of Technology, Shiraz, Iran. zarrinpoor@sutech.ac.ir.
Jazyk: angličtina
Zdroj: Health care management science [Health Care Manag Sci] 2024 Dec; Vol. 27 (4), pp. 555-579. Date of Electronic Publication: 2024 Oct 01.
DOI: 10.1007/s10729-024-09683-6
Abstrakt: Organ transplantation is one of the most complicated and challenging treatments in healthcare systems. Despite the significant medical advancements, many patients die while waiting for organ transplants because of the noticeable differences between organ supply and demand. In the organ transplantation supply chain, organ allocation is the most significant decision during the organ transplantation procedure, and kidney is the most widely transplanted organ. This research presents a novel method for assessing the efficiency and ranking of qualified organ-patient pairs as decision-making units (DMUs) for kidney allocation problem in the existence of COVID-19 pandemic and uncertain medical and logistical data. To achieve this goal, two-stage network data envelopment analysis (DEA) and credibility-based chance constraint programming (CCP) are utilized to develop a novel two-stage fuzzy network data envelopment analysis (TSFNDEA) method. The main benefits of the developed method can be summarized as follows: considering internal structures in kidney allocation system, investigating both medical and logistical aspects of the problem, the capability of expanding to other network structures, and unique efficiency decomposition under uncertainty. Moreover, in order to evaluate the validity and applicability of the proposed approach, a validation algorithm utilizing a real case study and different confidence levels is used. Finally, the numerical results indicate that the developed approach outperforms the existing kidney allocation system.
Competing Interests: Declarations. Conflict of interest: We confirm that there are no financial interests or support that could have appeared to influence the work reported in this paper.
(© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)
Databáze: MEDLINE
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