ArticleHealth care management science2016
The operating room case-mix problem under uncertainty and nurses capacity constraints.
Article in Health care management science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Article
- A hybrid analytical model for an entire hospital resource optimisation.Soft computing · 2021Article
- Analyzing economies of scale and scope in hospitals by use of case mix planning.Health care management science · 2020Article
- Facility Layout Planning with SHELL and Fuzzy AHP Method Based on Human Reliability for Operating Theatre.Journal of healthcare engineering · 2019Article
- Application of Operational Research Techniques in Operating Room Scheduling Problems: Literature Overview.Journal of healthcare engineering · 2018Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Surgery is one of the key functions in hospitals; it generates significant revenue and admissions to hospitals. In this paper we address the decision of choosing a case-mix for a surgery department. The objective of this study is to generate an optimal case-mix plan of surgery patients with uncertain surgery operations, which includes uncertainty in surgery durations, length of stay, surgery demand and the availability of nurses. In order to obtain an optimal case-mix plan, a stochastic optimization model is proposed and the sample average approximation method is applied. The proposed model is used to determine the number of surgery cases to be weekly served, the amount of operating rooms' time dedicated to each specialty and the number of ward beds dedicated to each specialty. The optimal case-mix selection criterion is based upon a weighted score taking into account both the waiting list and the historical demand of each patient category. The score aims to maximizing the service level of the operating rooms by increasing the total number of surgery cases that could be served. A computational experiment is presented to demonstrate the performance of the proposed method. The results show that the stochastic model solution outperforms the expected value problem solution. Additional analysis is conducted to study the effect of varying the number of ORs and nurses capacity on the overall ORs' performance.
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Registered trials
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