Elective Patient Admission and Scheduling under Multiple Resource Constraints

• 成果类型: Article
• 署名作者: Barz, Christiane; Rajaram, Kumar
• 署名单位: Technical University of Berlin; University of California System; University of California Los Angeles
• 刊物名称: PRODUCTION AND OPERATIONS MANAGEMENT
• ISSN/ISSBN: 1059-1478
• DOI: 10.1111/poms.12395
• 发表日期: 2015
• 页码: 1907-1930
• 关键词: patient admission; Patient Scheduling; multiple resources; Markov Decision Process; Approximate Dynamic Programming

摘要

We consider a patient admission problem to a hospital with multiple resource constraints (e. g., OR and beds) and a stochastic evolution of patient care requirements across multiple resources. There is a small but significant proportion of emergency patients who arrive randomly and have to be accepted at the hospital. However, the hospital needs to decide whether to accept, postpone, or even reject the admission from a random stream of non-emergency elective patients. We formulate the control process as a Markov decision process to maximize expected contribution net of overbooking costs, develop bounds using approximate dynamic programming, and use them to construct heuristics. We test our methods on data from the Ronald Reagan UCLA Medical Center and find that our intuitive newsvendor-based heuristic performs well across all scenarios.