{"title":"Optimizing hospital bed allocation for coordinated medical efficiency and quality improvement","authors":"Haiyue Yu, Ting Shen, Liwei Zhong","doi":"10.1007/s10878-024-01210-1","DOIUrl":null,"url":null,"abstract":"<p>In this study, we aim to optimize hospital bed allocation to enhance medical service efficiency and quality. We developed an optimization model and algorithms considering cross-departmental bed-sharing costs, patient waiting costs, and the impact on medical quality when patients are assigned to non-primary departments. First, we propose an algorithm to calculate departmental similarity and quantify the effect on patients’ length of stay when admitted to non-primary departments. We then formulate a two-stage cost minimization problem: the first stage involves determining bed allocation for each department, and the second stage involves dynamic admission control decisions. For the second stage, we apply a dynamic programming method and approximate the model using deterministic linear programming to ensure practicality and computational efficiency. Numerical studies validate the effectiveness of our approach. Results show that our model and algorithms significantly improve bed resource utilization and medical service quality, supporting hospital management decisions.</p>","PeriodicalId":50231,"journal":{"name":"Journal of Combinatorial Optimization","volume":"20 1","pages":""},"PeriodicalIF":0.9000,"publicationDate":"2024-10-21","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/s10878-024-01210-1","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
In this study, we aim to optimize hospital bed allocation to enhance medical service efficiency and quality. We developed an optimization model and algorithms considering cross-departmental bed-sharing costs, patient waiting costs, and the impact on medical quality when patients are assigned to non-primary departments. First, we propose an algorithm to calculate departmental similarity and quantify the effect on patients’ length of stay when admitted to non-primary departments. We then formulate a two-stage cost minimization problem: the first stage involves determining bed allocation for each department, and the second stage involves dynamic admission control decisions. For the second stage, we apply a dynamic programming method and approximate the model using deterministic linear programming to ensure practicality and computational efficiency. Numerical studies validate the effectiveness of our approach. Results show that our model and algorithms significantly improve bed resource utilization and medical service quality, supporting hospital management decisions.
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.