Tactical Resource Planning in Surgical Clinics
Doctoral thesis
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https://hdl.handle.net/11250/3113339Utgivelsesdato
2023Metadata
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Sammendrag
Due to demographic changes, many western countries experience a growing demand for health care and a stagnation in the working-age population. To maintain the level of care in the future, the health care resources must be better utilized. The main topic of research in my PhD is on tactical surgery planning, and we aim to develop tools that enhance resource efficiency in surgical clinics.
Tactical decisions facilitate the transfer of strategic objectives and decisions, to the operational planning of individual patients. The most frequently studied problem within tactical surgery planning, is the Master Surgery Scheduling Problem (MSSP). The MSS is a blueprint schedule where surgical specialties are assigned to operating room blocks thorough a planning cycle, aiming to achieves financial goals and serve patients in a timely manner.
In the first paper, we consider the problem of constructing an MSS for both planned and emergency surgeries. We face the trade-off between an efficient handling of planned surgeries, while ensuring responsive services for the emergencies. To face this trade-off, we develop a two-stage stochastic optimization model that accounts for the stochastic demand of emergency patients.
The second and third paper consider the integrated planning of the outpatient clinic and the operating theatre. Patients require services in both units, and the surgeons perform both consultations and surgeries. To facilitate a coordinated use of resources, we develop optimization models that account for the dependencies between the activities performed in the two units and that construct integrated master schedules. The third paper extends on the second paper, and here we propose a planning framework where parts of the master schedule is periodically refined to account for stochastic waiting lists.
The fourth paper is not considering surgery planning. It is based on a real-life project performed in March 2020, when St. Olav's Hospital was preparing for the COVID-19 pandemic. It was decided that all emergency patients that entered the hospital with a COVID-19 suspicion should be screened in the Emergency Department. We develop a discrete-event simulation model to estimate the impact on the Emergency Department and the ambulance services during the peak of the pandemic.
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Paper 1: Bovim, Thomas; Christiansen, Marielle; Gullhav, Anders Nordby; Range, Troels Martin; Hellemo, Lars. Stochastic master surgery scheduling. European Journal of Operational Research 2020 ;Volum 285.(2) s. 695-711. Copyright © Elsevier Ltd. Available at: http://dx.doi.org/10.1016/j.ejor.2020.02.001Paper 2: Bovim, Thomas; Abdullahu, Anita; Andersson, Henrik; Gullhav, Anders Nordby. Integrated master surgery and outpatient clinic scheduling. Operations Research for Health Care 2022 ;Volum 35. s. - © 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license. Available at: http://dx.doi.org/10.1016/j.orhc.2022.100358
Paper 3: Bovim, Thomas; Gullhav, Anders Nordby; Andersson, Henrik; A. Riise. A framework for integrated resource planning in surgical clinics. This paper is submitted for publication and is therefore not included.
Paper 4: Bovim, Thomas; Gullhav, Anders Nordby; Andersson, Henrik; Dale, Jostein; Karlsen, Kjetil Andreas Hognestad. Simulating emergency patient flow during the COVID-19 pandemic. Journal of Simulation 2021 s. - © 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. . This is an open access article under the CC BY-NC-ND license. Available at: http://dx.doi.org/10.1080/17477778.2021.2015259