Multicriteria optimization techniques for understanding the case mix landscape of a hospital

• DOI: 10.1016/j.ejor.2024.05.030
• Publication Date: 2024-06-07T17:05:05Z
• Authors: Robert L Burdett; Paul Corry; Prasad Yarlagadda; David Cook; Sean Birgan
• Keywords: FOS: Computer and information sciences; Artificial Intelligence (cs.AI); Computer Science - Artificial Intelligence; 3. Good health

Various medical and surgical units operate in a typical hospital to treat their patients these compete for infrastructure like operating rooms (OR) ward beds. How that competition is regulated affects the capacity output of hospital. This article considers impact treating different patient case mix (PCM). As each has an economic consequence unique profile resource usage, this consideration important. To better understand landscape identify those which are optimal from utilisation perspective, improved multicriteria optimization (MCO) approach proposed. there many types hospital, task generating archive non-dominated (i.e., Pareto optimal) computationally challenging. generate archive, parallelised epsilon constraint method (ECM) introduced. Our parallel random corrective significantly faster than prior methods not restricted evaluating points on structured uniform mesh. such we can more solutions. The application KD-Trees another new contribution. We use them perform proximity testing store high dimensional frontier (PF). For generating, viewing, navigating, querying development suitable decision support tool (DST) proposed demonstrated.