印度拉贾斯坦邦肾移植系统的离散事件模拟模型。

IF 1.2 Q4 HEALTH POLICY & SERVICES Health Systems Pub Date : 2020-11-28 eCollection Date: 2022-01-01 DOI:10.1080/20476965.2020.1848355
Mohd Shoaib, Utkarsh Prabhakar, Sumit Mahlawat, Varun Ramamohan
{"title":"印度拉贾斯坦邦肾移植系统的离散事件模拟模型。","authors":"Mohd Shoaib,&nbsp;Utkarsh Prabhakar,&nbsp;Sumit Mahlawat,&nbsp;Varun Ramamohan","doi":"10.1080/20476965.2020.1848355","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":44699,"journal":{"name":"Health Systems","volume":"11 1","pages":"30-47"},"PeriodicalIF":1.2000,"publicationDate":"2020-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/20476965.2020.1848355","citationCount":"0","resultStr":"{\"title\":\"A discrete-event simulation model of the kidney transplantation system in Rajasthan, India.\",\"authors\":\"Mohd Shoaib,&nbsp;Utkarsh Prabhakar,&nbsp;Sumit Mahlawat,&nbsp;Varun Ramamohan\",\"doi\":\"10.1080/20476965.2020.1848355\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":44699,\"journal\":{\"name\":\"Health Systems\",\"volume\":\"11 1\",\"pages\":\"30-47\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2020-11-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/20476965.2020.1848355\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Health Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/20476965.2020.1848355\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2022/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q4\",\"JCRName\":\"HEALTH POLICY & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Health Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/20476965.2020.1848355","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/1/1 0:00:00","PubModel":"eCollection","JCR":"Q4","JCRName":"HEALTH POLICY & SERVICES","Score":null,"Total":0}
引用次数: 0

摘要

我们提出了印度拉贾斯坦邦肾移植系统的离散事件模拟模型。器官是根据普通人群的器官捐献率在全州范围内产生的,并分配给肾移植等待名单上的患者。器官分配算法是根据官方发布的肾移植指南开发的,模型参数是尽可能使用公开可用的数据估计的。该模型产生的移植结果包括:(a)患者在登记后一至五年内接受器官的概率和(b)由于缺乏捐赠器官而每年死亡的平均人数。还进行了模拟实验,观察增加器官到达率和建立额外的移植中心对移植结果的影响。我们还演示了使用这样的模型,以最佳地定位额外的移植中心使用模拟优化方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
A discrete-event simulation model of the kidney transplantation system in Rajasthan, India.

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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Health Systems
Health Systems HEALTH POLICY & SERVICES-
CiteScore
4.20
自引率
11.10%
发文量
20
期刊最新文献
Towards new frontiers of healthcare systems research using artificial intelligence and generative AI. Assistance systems for patient positioning in radiotherapy practice. Resilience of hospitals in an age of disruptions: a systematic literature review on resources and capabilities. From digital health to learning health systems: four approaches to using data for digital health design. Using participatory systems approaches to improve healthcare delivery.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1