基于遗传算法的战略规划框架,用于优化新西兰Northland的一般做法的可及性和成本

IF 1.2 Q4 HEALTH POLICY & SERVICES
Health Systems Pub Date : 2023-02-16 eCollection Date: 2023-01-01 DOI:10.1080/20476965.2023.2174454
Fulvio D Lopane, Melanie Reuter-Oppermann, Andrea Raith, Daniel J Exeter, Ilze Ziedins, Richard Dawson
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引用次数: 0

摘要

全科医生(GP)短缺是全世界面临的一项挑战,不仅在欧洲如此,在新西兰等国也是如此。在农村地区提供初级医疗服务尤其具有挑战性。为了向决策者提供支持,有必要首先评估当前全科医生的覆盖率,然后确定未来的不同方案和计划。在本文中,我们首先全面概述了有关全科医生诊所选址的相关文献。其次,我们提出了一种基于遗传算法框架评估全科医生覆盖率和确定未来全科医生位置的方法。我们选择了新西兰北地农村地区作为使用案例。我们还对主要输入参数进行了敏感性分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A genetic algorithm-based strategic planning framework for optimising accessibility and costs of general practices in Northland, New Zealand.

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.

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来源期刊
Health Systems
Health Systems HEALTH POLICY & SERVICES-
CiteScore
4.20
自引率
11.10%
发文量
20
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