Journal article
Minimising the number of cancellations at the time of a severe lack of postanesthesia care unit beds or nurses
International journal of production research, Vol.60(11), pp.3383-3396
2022
DOI: 10.1080/00207543.2021.1921874
Abstract
A deficiency of the postanesthesia care unit (PACU) beds or nurses may cause delays in the operating rooms (ORs) and increase the number of cancellations. Some disruptions like the COVID-19 pandemic may cause this deficiency. This paper investigates two integrated OR and PACU scheduling problems; one with few PACU beds, and the other with few PACU nurses. For each problem, a mathematical model and a matheuristic are proposed for minimising the number of cancellations. To the best of our knowledge, it is the first study that investigates the implications of a severe lack of the PACU beds or nurses on the number of cancellations. The matheuristics hybridise the decomposition of each instance into some small-sized sub-instances with a variable neighbourhood search algorithm. The main advantages of these methods are their flexibility to incorporate many problem details (such as a step-wise demand for the PACU nurses) and to solve any large-scale problem. Numerical results for a data set with 22 ORs show that with an increasingly severe lack of PACU capacity there is progressively greater benefit of the matheuristics than their initial solutions. Moreover, these results show the influence of the overtime and the recovery in ORs on improving the situation.
Details
- Title: Subtitle
- Minimising the number of cancellations at the time of a severe lack of postanesthesia care unit beds or nurses
- Creators
- Danial Khorasanian - Department of Industrial and Systems Engineering, Isfahan University of TechnologyFranklin Dexter - Department of Anesthesia, University of IowaErik Demeulemeester - Faculty of Business and Economics, Research Center for Operations Management, KU LeuvenGhasem Moslehi - Department of Industrial and Systems Engineering, Isfahan University of Technology
- Resource Type
- Journal article
- Publication Details
- International journal of production research, Vol.60(11), pp.3383-3396
- DOI
- 10.1080/00207543.2021.1921874
- ISSN
- 0020-7543
- eISSN
- 1366-588X
- Publisher
- Taylor & Francis
- Language
- English
- Electronic publication date
- 05/06/2021
- Date published
- 2022
- Academic Unit
- Health Management and Policy; Anesthesia
- Record Identifier
- 9984077784402771
Metrics
21 Record Views