Lopane, FD;
Reuter-Oppermann, M;
Raith, A;
Exeter, DJ;
Ziedins, I;
Dawson, R;
(2023)
A genetic algorithm-based strategic planning framework for optimising accessibility and costs of general practices in Northland, New Zealand.
Health Systems
, 12
(3)
pp. 332-356.
10.1080/20476965.2023.2174454.
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Abstract
Shortage of general practitioners (GP) is a challenge worldwide, not only in Europe, but also in countries like New Zealand. Providing primary care in rural areas is especially challenging. In order to support decision makers, it is necessary to first assess the current GP coverage and then to determine different scenarios and plans for the future. In this paper, we first present a thorough overview of related literature on locating GP practices. Second, we propose an approach for assessing the GP coverage and determining future GP locations based on a genetic algorithm framework. As a use case, we have chosen the rural New Zealand region of Northland. We also perform a sensitivity analysis for the main input parameters.
| Type: | Article |
|---|---|
| Title: | A genetic algorithm-based strategic planning framework for optimising accessibility and costs of general practices in Northland, New Zealand |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1080/20476965.2023.2174454 |
| Publisher version: | https://doi.org/10.1080/20476965.2023.2174454 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | General practitioners, spatial optimisation, New Zealand, decision support |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Centre for Advanced Spatial Analysis |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10166496 |
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