Managing surgical waiting lists through dynamic priority scoring

Jack Powers (), James M. McGree, David Grieve, Ratna Aseervatham, Suzanne Ryan and Paul Corry
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Jack Powers: Queensland University of Technology
James M. McGree: Queensland University of Technology
David Grieve: Sunshine Coast University Hospital
Ratna Aseervatham: Sunshine Coast University Hospital
Suzanne Ryan: Sunshine Coast University Hospital
Paul Corry: Queensland University of Technology

Health Care Management Science, 2023, vol. 26, issue 3, No 9, 533-557

Abstract: Abstract Prioritising elective surgery patients under the Australian three-category system is inherently subjective due to variability in clinician decision making and the potential for extraneous factors to influence category assignment. As a result, waiting time inequities can exist which may lead to adverse health outcomes and increased morbidity, especially for patients deemed to be low priority. This study investigated the use of a dynamic priority scoring (DPS) system to rank elective surgery patients more equitably, based on a combination of waiting time and clinical factors. Such a system enables patients to progress on the waiting list in a more objective and transparent manner, at a rate relative to their clinical need. Simulation results comparing the two systems indicate that the DPS system has potential to assist in managing waiting lists by standardising waiting times relative to urgency category, in addition to improving waiting time consistency for patients of similar clinical need. In clinical practice, this system is likely to reduce subjectivity, increase transparency, and improve overall efficiency of waiting list management by providing an objective metric to prioritise patients. Such a system is also likely to increase public trust and confidence in the systems used to manage waiting lists.

Keywords: Simulation; Waiting list; Elective surgery; Patient prioritisation; Genetic algorithm; Multi-criteria decision-making; Equity in treatment; Operations research; Operations management (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10729-023-09648-1

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