A genetic algorithm-based strategic planning framework for optimising accessibility and costs of general practices in Northland, New Zealand.
A genetic algorithm-based strategic planning framework for optimising accessibility and costs of general practices in Northland, New Zealand.
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基于遗传算法的战略规划框架，用于优化新西兰北部地区一般医疗的可及性和成本。
DOI：
10.1080/20476965.2023.2174454
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发表时间：
2023
期刊：
影响因子：
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通讯作者：
Lopane FD
中科院分区：
文献类型：
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作者：
Lopane FD
全科医生（GP）短缺是一个全球性的挑战，不仅在欧洲，在新西兰等国家也是如此。在农村地区提供初级保健尤其具有挑战性。为了支持决策者，有必要首先评估当前的全科医生覆盖率，然后确定未来的不同情景和计划。在本文中，我们首先提出了一个全面概述的相关文献定位GP实践。其次，我们提出了一种基于遗传算法框架的GP覆盖率评估和未来GP位置确定方法。作为一个用例，我们选择了Northland的新西兰农村地区。我们还对主要输入参数进行了灵敏度分析。
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.