BACKGROUND Detecting the variation of health indicators across similar areas or peer geographies is often useful if the spatial units are socially and economically meaningful, so that there is a degree of homogeneity in each unit. Indices are frequently constructed to generate summaries of socioeconomic status or other measures in geographic small areas. Larger areas may be built to be homogenous using regionalization algorithms. However, there are no explicit guidelines in the literature for the grouping of peer geographies based on measures such as area level socioeconomic indices. Moreover, the use of an index score becomes less meaningful as the size of an area increases. This paper introduces an easy to use statistical framework for the identification and classification of homogeneous areas. We propose the Homogeneity and Location indices to measure the concentration and central value respectively of an areas' socioeconomic distribution. We also provide a transparent set of criteria that a researcher can follow to establish whether a set of proposed geographies are acceptably homogeneous or need further refining. RESULTS We applied our framework to assess the socioeconomic homogeneity of the commonly used SA3 Australian census geography. These results showed that almost 60% of the SA3 census units are likely to be socioeconomically heterogeneous and hence inappropriate for presenting area level socioeconomic disadvantage. We also showed that the Location Index is a more robust descriptive measure of the distribution compared to other measures of central tendency. Finally, the methodology proposed was used to analyse the age-standardized variation of GP attenders in a metropolitan area. The results suggest that very high GP attenders (20+ visits) live in SA3s with the most socioeconomic disadvantage. The findings revealed that households with low income and families with children and jobless parents are the major drivers for discerning disadvantaged communities. CONCLUSION Reporting indicators rates for geographies grouped according to similarity may be useful for the analysis of geographic variation. The use of a framework for the identification of meaningful peer geographies would be beneficial to health planners and policy makers by providing realistic and valid peer group geographies.

中文翻译：

---

在医疗保健变化分析中对同质社会经济区域进行识别和分类的框架。


背景技术如果空间单元具有社会和经济意义，从而在每个单元中存在一定程度的同质性，则检测相似区域或同等地理区域之间的健康指标的变化通常是有用的。经常构建指数来生成小地理区域的社会经济状况或其他衡量标准的摘要。使用区域化算法可以将更大的区域构建为同质的。然而，文献中没有明确的指导方针来根据地区级社会经济指数等指标对同行地理进行分组。此外，随着区域大小的增加，索引分数的使用变得越来越没有意义。本文介绍了一种易于使用的统计框架，用于识别和分类同质区域。我们提出同质性和位置指数来分别衡量一个地区社会经济分布的集中度和中心值。我们还提供了一套透明的标准，研究人员可以遵循这些标准来确定一组拟议的地理区域是否具有可接受的同质性或需要进一步完善。结果 我们应用我们的框架来评估常用的 SA3 澳大利亚人口普查地理的社会经济同质性。这些结果表明，近 60% 的 SA3 人口普查单位可能存在社会经济异质性，因此不适合呈现地区层面的社会经济劣势。我们还表明，与其他集中趋势度量相比，位置指数是一种更稳健的分布描述性度量。最后，所提出的方法用于分析大都市区全科医生参加者的年龄标准化变化。 结果表明，非常多的全科医生参加者（20 次以上就诊）居住在社会经济最不利的 SA3 地区。调查结果显示，低收入家庭、有孩子的家庭和失业父母是识别弱势社区的主要推动力。结论 根据相似性分组的地理报告指标率可能有助于分析地理变化。使用一个框架来识别有意义的同行地域，通过提供现实和有效的同行群体地域，将有利于卫生规划者和政策制定者。