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arXiv · 2607.25482

Integrated Framework for Long-term Elective Surgery Management under Uncertainty: From Strategic to Tactical Planning

Abstract

In public healthcare systems, elective surgery waiting lists are a persistent management challenge, as hospitals must balance limited operating theatre capacity with uncertain and evolving demand. Long-term planning for these lists requires more than assigning operating theatre (OT) time to medical specialities, as isolated allocation decisions may fail to stabilise waiting lists over time. Such planning must account for uncertainty in patient arrivals in the queue and surgery durations, which are often neglected in OT scheduling models. In this context, we propose a novel integrated framework for elective surgery management under uncertainty, linking strategic queue-control decisions with tactical OT scheduling. The framework combines three components: (i) a closed-loop control policy that determines the number of patients to schedule in each planning cycle; (ii) a model to account for overtime-related cancellation risks; and (iii) a mixed-integer linear programming formulation, informed by the previous components, to solve an OT Scheduling Problem. The resulting tactical schedules are therefore guided by the long-term evolution of speciality-specific queues and by cancellation-risk considerations. We evaluate the proposed framework through a case study at University Hospital Unicamp, a large Brazilian public referral hospital. The results show that integrating strategic and tactical decisions stabilises waiting lists, controls cancellation risks, and supports more transparent theatre-allocation decisions, while remaining computationally efficient for practical implementation.

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BibTeXRIS

Joao P. F. da Silva, Lucas Bortoletto, Rafael C. S. Schouery, Edilson F. Arruda, Fabricio F. Santos, Ana Paula C. I. Alves. 2026-07-28. Integrated Framework for Long-term Elective Surgery Management under Uncertainty: From Strategic to Tactical Planning. https://arxiv.org/abs/2607.25482

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