A mixed integer linear programing approach to perform hospital capacity assessments

, , Sinnott, Michael, Cook, David, & (2017) A mixed integer linear programing approach to perform hospital capacity assessments. Expert Systems with Applications, 77, pp. 170-188.

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Description

An approach to perform a system wide analysis of hospital resources and capacity has been developed. Embedded within an intelligent system it would provide planners and management capability to strategically improve the efficiency of their hospitals today and a means to create more efficient hospitals in the future. In theory this approach can help hospitals with a variety of capacity planning and resource allocation activities. On a day to day basis it can be used to perform a variety of important capacity querying activities. In addition it can be used to predict the future performance of a hospital and the effect of structural and parametric changes within the hospital. The approach consists of a mixed integer linear programming (MILP) model and a number of advanced extensions. The MILP models can determine the maximum number of patients of each type that can be treated within a given period of time or the time required to process a given cohort of patients. A case study of a large public hospital has been performed to validate our approach. Extensive numerical investigations successfully demonstrate the applicability of the approach to real sized health care applications and the great potential for further research and development on this topic.

Impact and interest:

26 citations in Scopus
17 citations in Web of Science®
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ID Code: 98721
Item Type: Contribution to Journal (Journal Article)
Refereed: Yes
ORCID iD:
Burdett, Robertorcid.org/0000-0003-2484-3646
Kozan, Erhanorcid.org/0000-0002-3208-702X
Tian, Glenorcid.org/0000-0002-8709-5625
Measurements or Duration: 19 pages
Keywords: Capacity analysis, Capacity querying, Health care, Hospital resource planning, Hospitals, Theoretical capacity
DOI: 10.1016/j.eswa.2017.01.050
ISSN: 0957-4174
Pure ID: 33199064
Divisions: Past > Institutes > Institute for Future Environments
Past > QUT Faculties & Divisions > Science & Engineering Faculty
Current > Schools > School of Mathematical Sciences
Funding:
Copyright Owner: Consult author(s) regarding copyright matters
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Deposited On: 30 Jan 2017 22:23
Last Modified: 04 Jul 2024 16:50