A discrete-event simulation model of the kidney transplantation system in Rajasthan, India

Mohd Shoaib, Utkarsh Prabhakar, Sumit Mahlawat and Varun Ramamohan

Health Systems, 2022, vol. 11, issue 1, 30-47

Abstract: We present a discrete-event simulation model of the kidney transplantation system in an Indian state, Rajasthan. Organs are generated across the state based on the organ donation rate among the general population, and are allocated to patients on the kidney transplantation waitlist. The organ allocation algorithm is developed using official guidelines published for kidney transplantation, and model parameters were estimated using publicly available data to the extent possible. Transplantation outcomes generated by the model include: (a) the probabilities of a patient receiving an organ within one to 5 years of registration and (b) the average number of deaths per year due to lack of donated organs. Simulation experiments involving observing the effect of increasing the organ arrival rate and establishing additional transplantation centres on transplantation outcomes are also conducted. We also demonstrate the use of such a model to optimally locate additional transplantation centres using simulation optimisation methods.

Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/20476965.2020.1848355 (text/html)
Access to full text is restricted to subscribers.

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:taf:thssxx:v:11:y:2022:i:1:p:30-47

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/thss20

DOI: 10.1080/20476965.2020.1848355

Access Statistics for this article

Health Systems is currently edited by Sally Brailsford

More articles in Health Systems from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().