Evans, Luke, Acton, Jennifer H.  ORCID: https://orcid.org/0000-0002-0347-7651, Hiscott, Carla and Gartner, Daniel ORCID: https://orcid.org/0000-0003-4361-8559
2023.
An operations research approach to automated patient scheduling for eye care using a multi-criteria decision support tool.
Scientific Reports
13
, 553.
10.1038/s41598-022-26755-1
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Abstract
Inefficient management of resources and waiting lists for high-risk ophthalmology patients can contribute to sight loss. The aim was to develop a decision support tool which determines an optimal patient schedule for ophthalmology patients. Our approach considers available booking slots as well as patient-specific factors. Using standard software (Microsoft Excel and OpenSolver), an operations research approach was used to formulate a mathematical model. Given a set of patients and clinic capacities, the model objective was to schedule patients efficiently depending on eyecare measure risk factors, referral-to-treatment times and targets, patient locations and slot availabilities over a pre-defined planning horizon. Our decision support tool can feedback whether or not a patient is scheduled. If a patient is scheduled, the tool determines the optimal date and location to book the patients’ appointments, with a score provided to show the associated value of the decisions made. Our dataset from 519 patients showed optimal prioritization based on location, risk of serious vision loss/damage and the referral-to-treatment time. Given the constraints of available slots, managers can input hospital-specific parameters such as demand and capacity into our model. The model can be applied and implemented immediately, without the need for additional software, to generate an optimized patient schedule.
| Item Type: | Article |
|---|---|
| Date Type: | Published Online |
| Status: | Published |
| Schools: | Schools > Mathematics Schools > Optometry and Vision Sciences |
| Publisher: | Nature Research |
| ISSN: | 2045-2322 |
| Date of First Compliant Deposit: | 10 January 2023 |
| Date of Acceptance: | 20 December 2022 |
| Last Modified: | 20 May 2023 06:18 |
| URI: | https://orca.cardiff.ac.uk/id/eprint/155621 |
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