{"title":"Impact of payment schemes on performance in a medical cost-sharing system: bundled payment vs. total prepayment","authors":"Miao Yu, Wang Zhou, Yu Zhao","doi":"10.1007/s10878-025-01301-7","DOIUrl":null,"url":null,"abstract":"<p>Currently, many countries are on the process of reforming their health care payment systems from post-payment to pre-payment. To explore the impact of pre-payment schemes on health system performance we investigate the two payment schemes, bundled payment (BP) and total prepayment (TP), on performance in a medical cost-sharing system. Under the BP scheme, the government compensates hospitals with a lump sum for the entire course of each patient’s care. Under the TP scheme, the government provides the total amount of integrated compensation within a period. A three Stackelberg game with an embedded queueing model is used to explore the interactions among participants: government, hospital, and patients. The government determines the compensation received by hospitals and the copayment paid by patients to maximize social welfare. Next, the hospital determines its service rate for each medical episode to maximize profit. Last, patients make decisions on whether to appeal to the hospital for medical services. We derive the optimal strategy for the participants under the BP and TP schemes, and compare the system performance through numerical analysis. Results show that BP is better than TP in reducing patient expected waiting time, while it outperforms TP in terms of system accessibility and service quality. Our study is the first to consider the total prepayment scheme in the healthcare system decision analysis and the findings offer important insights for policymakers regarding implementing medical insurance reform in practice.</p>","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"57 1","pages":""},"PeriodicalIF":1.1000,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Combinatorial Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10878-025-01301-7","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Currently, many countries are on the process of reforming their health care payment systems from post-payment to pre-payment. To explore the impact of pre-payment schemes on health system performance we investigate the two payment schemes, bundled payment (BP) and total prepayment (TP), on performance in a medical cost-sharing system. Under the BP scheme, the government compensates hospitals with a lump sum for the entire course of each patient’s care. Under the TP scheme, the government provides the total amount of integrated compensation within a period. A three Stackelberg game with an embedded queueing model is used to explore the interactions among participants: government, hospital, and patients. The government determines the compensation received by hospitals and the copayment paid by patients to maximize social welfare. Next, the hospital determines its service rate for each medical episode to maximize profit. Last, patients make decisions on whether to appeal to the hospital for medical services. We derive the optimal strategy for the participants under the BP and TP schemes, and compare the system performance through numerical analysis. Results show that BP is better than TP in reducing patient expected waiting time, while it outperforms TP in terms of system accessibility and service quality. Our study is the first to consider the total prepayment scheme in the healthcare system decision analysis and the findings offer important insights for policymakers regarding implementing medical insurance reform in practice.
期刊介绍:
The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering.
The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.