Cluster for Resilience and Wellbeing, Appleton and Manna Institutes, Central Queensland University, Brisbane, QLD 4701, Australia.
Violet Vines Marshman Centre for Rural Health Research, La Trobe University, Bendigo, VIC 3550, Australia.
Int J Environ Res Public Health. 2024 Mar 13;21(3):340. doi: 10.3390/ijerph21030340.
Since 2006, the Australian Aboriginal and Torres Strait Islander Health Performance Framework (HPF) reports have provided information about Indigenous Australians' health outcomes. The HPF was designed, in consultation with Indigenous stakeholder groups, to promote accountability and inform policy and research. This paper explores bridging the HPF as a theoretical construct and the publicly available data provided against its measures. A whole-of-framework, whole-of-system monitoring perspective was taken to summarise 289 eligible indicators at the state/territory level, organised by the HPF's tier and group hierarchy. Data accompanying the 2017 and 2020 reports were used to compute improvement over time. Unit change and confidence indicators were developed to create an abstract but interpretable improvement score suitable for aggregation and visualisation at scale. The result is an exploratory methodology that summarises changes over time. An example dashboard visualisation is presented. The use of secondary data inevitably invites acknowledgments of what analysis cannot say, owing to methods of collection, sampling bias, or unobserved variables and the standard mantra regarding correlation not being causation (though no attempt has been made here to infer relationships between indicators, groups, or tiers). The analysis presented questions the utility of the HPF to inform healthcare reform.
自 2006 年以来,澳大利亚原住民和托雷斯海峡岛民健康绩效框架 (HPF) 报告提供了有关澳大利亚原住民健康结果的信息。HPF 是在与原住民利益相关者团体协商后设计的,旨在促进问责制并为政策和研究提供信息。本文探讨了将 HPF 作为理论结构与根据其措施提供的公开可用数据联系起来的问题。采用全框架、全系统监测的观点,对按 HPF 层级和群组层次组织的 289 个符合条件的指标进行了总结。使用 2017 年和 2020 年报告中的数据来计算随时间的改进情况。开发了单位变化和置信度指标,以创建一个抽象但可解释的改进分数,适合在大规模进行聚合和可视化。结果是一种探索性方法,可总结随时间的变化。展示了一个示例仪表板可视化。由于收集方法、抽样偏差或未观察到的变量,以及相关性并不意味着因果关系的标准格言(尽管这里没有试图推断指标、组或层级之间的关系),因此使用二次数据不可避免地需要承认分析无法说明的问题。所提出的分析对 HPF 为医疗保健改革提供信息的效用提出了质疑。