INTEGRATED SURGERY PLANNING AND BED ALLOCATION WITH MULTIPLE ROUTES OF POST-SURGICAL CARE, WITH APPLICATION TO A MILITARY HOSPITAL’S ORTHOPAEDIC DEPARTMENT
ABSTRACT This paper presents na integrated surgery scheduling and post-surgical bed planning problem for a standard hospital setting. The setting gives rise to a general healthcare modelling problem with a number of innovations with respect to the literature. The model includes multiple post-surgical recovery trajectories involving possible stays at the intensive (ICU) or semi-intensive care unit (SICU) and allows the decision maker to assign a bed allocation plan that considers the maximum length of stays at both SICU and ICU. The approach is designed to ensure a seamless patient flow, avoiding surgery cancellations due to insufficient downstream resources, and enables tactical planning that considers the long-term balance between demand and surgery provision across all specialities. To validate the model and investigate the sensitivity with respect to model parameters and the availability of resources, we use a series of experiments that were based on the actual operation of a military hospital’s orthopaedic department. The results illustrate the demand pressures, as na optimised allocation with the current demand and resources results in na occupation of 96.5%. We also show that increases in demand should be matched by a similar percentage increase in operating theatre capacity in order to keep the occupation below 100%.
Authors
- Edilson F. Arruda (ORCID: https://orcid.org/0000-0002-9835-352X)
- Laura Bahiense (ORCID: https://orcid.org/0000-0001-8175-8320)
- Virgílio José Martins Ferreira Filho (ORCID: https://orcid.org/0000-0002-3432-5212)
- Gustavo Carneiro (ORCID: https://orcid.org/0009-0006-4389-371X)
Institutions
- Universidade Federal do Rio de Janeiro (BR)
- Brazilian Naval School (BR)
Publication Details
- Journal
- Pesquisa Operacional
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1590/0101-7438.2025.045.00284818
- Primary Topic
- Healthcare Operations and Scheduling Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00