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Measuring geographic access to health care: raster and network-based methods

机译:衡量获得医疗保健的地理区域:基于栅格和网络的方法

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Background Inequalities in geographic access to health care result from the configuration of facilities, population distribution, and the transportation infrastructure. In recent accessibility studies, the traditional distance measure (Euclidean) has been replaced with more plausible measures such as travel distance or time. Both network and raster-based methods are often utilized for estimating travel time in a Geographic Information System. Therefore, exploring the differences in the underlying data models and associated methods and their impact on geographic accessibility estimates is warranted. Methods We examine the assumptions present in population-based travel time models. Conceptual and practical differences between raster and network data models are reviewed, along with methodological implications for service area estimates. Our case study investigates Limited Access Areas defined by Michigan’s Certificate of Need (CON) Program. Geographic accessibility is calculated by identifying the number of people residing more than 30 minutes from an acute care hospital. Both network and raster-based methods are implemented and their results are compared. We also examine sensitivity to changes in travel speed settings and population assignment. Results In both methods, the areas identified as having limited accessibility were similar in their location, configuration, and shape. However, the number of people identified as having limited accessibility varied substantially between methods. Over all permutations, the raster-based method identified more area and people with limited accessibility. The raster-based method was more sensitive to travel speed settings, while the network-based method was more sensitive to the specific population assignment method employed in Michigan. Conclusions Differences between the underlying data models help to explain the variation in results between raster and network-based methods. Considering that the choice of data model/method may substantially alter the outcomes of a geographic accessibility analysis, we advise researchers to use caution in model selection. For policy, we recommend that Michigan adopt the network-based method or reevaluate the travel speed assignment rule in the raster-based method. Additionally, we recommend that the state revisit the population assignment method.
机译:背景设施的配置,人口分布和交通基础设施,导致无法获得地理上的医疗保健机会。在最近的可及性研究中,传统的距离量度(欧几里得)已被更合理的量度取代,例如旅行距离或时间。基于网络和基于栅格的方法通常都用于估计地理信息系统中的旅行时间。因此,有必要探索基础数据模型和关联方法的差异及其对地理可访问性估计的影响。方法我们研究基于人口的旅行时间模型中存在的假设。审查了栅格数据模型和网络数据模型之间的概念和实际差异,以及对服务区估计的方法学含义。我们的案例研究调查了密歇根州的需求证明(CON)计划所定义的限制进入区域。地理可及性是通过识别在急诊医院居住30分钟以上的人数来计算的。实现了基于网络和基于栅格的方法,并比较了它们的结果。我们还研究了旅行速度设置和人口分配变化的敏感性。结果在这两种方法中,被确定为具有有限可达性的区域在位置,配置和形状上都是相似的。然而,被确定为具有有限可达性的人数在两种方法之间存在很大差异。在所有排列中,基于栅格的方法确定了更多的区域和可访问性有限的人员。基于栅格的方法对行进速度设置更敏感,而基于网络的方法对密歇根州采用的特定人口分配方法更敏感。结论基础数据模型之间的差异有助于解释栅格方法和基于网络的方法之间的结果差异。考虑到数据模型/方法的选择可能会大大改变地理可及性分析的结果,因此我们建议研究人员在选择模型时要谨慎。对于政策,我们建议密歇根州采用基于网络的方法,或者在基于栅格的方法中重新评估行驶速度分配规则。此外,我们建议州重新考虑人口分配方法。

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