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一种基于遗传算法的战略规划框架,用于优化新西兰北地地区全科医疗服务的可及性和成本。

A genetic algorithm-based strategic planning framework for optimising accessibility and costs of general practices in Northland, New Zealand.

作者信息

Lopane Fulvio D, Reuter-Oppermann Melanie, Raith Andrea, Exeter Daniel J, Ziedins Ilze, Dawson Richard

机构信息

Centre for Advanced Spatial Analysis, University College London, London, UK.

Information Systems group, Department of Law and Economics, Technical University of Darmstadt, Darmstadt, Germany.

出版信息

Health Syst (Basingstoke). 2023 Feb 16;12(3):332-356. doi: 10.1080/20476965.2023.2174454. eCollection 2023.

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.

摘要

全科医生短缺是一个全球性挑战,不仅在欧洲如此,在新西兰等国家也是如此。在农村地区提供初级医疗服务尤其具有挑战性。为了支持决策者,有必要首先评估当前的全科医生覆盖情况,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关于全科医生执业地点的相关文献。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情况并确定未来全科医生执业地点的方法。作为一个案例,我们选择了新西兰北地的农村地区。我们还对主要输入参数进行了敏感性分析。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1d7b/10583631/08c1e80b37ff/THSS_A_2174454_UF0001_OC.jpg

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