Designing utilization-based spatial healthcare accessibility decision support systems: A case of a regional health plan

Designing utilization-based spatial healthcare accessibility decision support systems: A case of a regional health plan
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DOI:
10.1016/j.dss.2017.05.011
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发表时间:
2017-07-01
影响因子:
7.5
通讯作者:
Fick, Genia
Fick, Genia
中科院分区:
计算机科学1区
文献类型:
--
作者:
Li, Yan;Vo, Au;Fick, Genia

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在美国,无数的医疗改革已经开始显示出一些积极的影响,使“潜在的获取”成为可能。获得保健服务的一个方面,即“有机会”,即为周围人口提供和获得保健服务,尚未得到充分解决。关于“获取”的研究目前由一系列称为浮动集水区(FCA)的方法所倡导。然而,现有的学术研究在FCA方法中整合非空间因素方面受到限制。本研究首次尝试以卫生服务使用行为模型为理论视角,将非空间因素整合到空间卫生服务可达性研究中。该框架采用了一种独特的方法,通过预测分析为不同人口亚组的医疗保健需求导出分类和因素权重。采用区域卫生计划的个案研究对拟议的框架进行评估。空间决策支持系统(SDSS)实例化了框架,使决策者能够探索医生短缺的领域。SDSS验证了所提出的基于利用率的框架的实用性,并随后允许在实际应用中实施其他FCA方法。(C) 2017 Elsevier B.V.版权所有
In the U.S., myriad healthcare reforms have begun to show some positive effects on enabling "potential access". One facet of healthcare access, "having access", which is the availability and accessibility of health services for the surrounding populations, has not been adequately addressed. Research regarding "having access" is presently championed by a family of methods called Floating Catchment Area (FCA). However, existing scholarship is limited in integrating non-spatial factors within the FCA methods. In this research, we propose a novel utilization based framework as the first attempt to adopt the Behavioral Model of Health Services Use as a theoretical lens to integrate non-spatial factors in spatial healthcare accessibility research. The framework employs a unique approach to derive categorical and factor weights for different population subgroup's healthcare needs using predictive analytics. The proposed framework is evaluated using a case study of a regional health plan. A Spatial Decision Support System (SDSS) instantiates the framework and enables decision makers to explore physician shortage areas. The SDSS validates the practicality of the proposed utilization-based framework and subsequently allows other FCA methods to be implemented in real-world applications. (C) 2017 Elsevier B.V. All rights reserved.