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首页> 外文期刊>International journal on disability and human development : >Developing 'policy stories' for state health system benchmarking: a small-/V quali-quantitative study
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Developing 'policy stories' for state health system benchmarking: a small-/V quali-quantitative study

机译:为州卫生系统基准制定“政策故事”:一项小型/ V定性研究

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Background: The benchmarking literature has made important advances and offers many different population health indicators that can be used to compare state health systems. However, there is still a need for qualitative, complexity-oriented approaches that allow policy-makers to develop explanatory 'policy stories' from combining such indicators that are useful to policy solutions. Methods: A new qualitative method from the social sciences based on Boolean approaches, called Qualitative Comparative Analysis (QCA), was piloted in a 'real world, policy consultancy to combine Australian state-level indicators of community and health system inputs, interventions, and population health outcomes. Analyses were provided for state inputs and outcomes in a specific area of chronic disease (mental health), along with state profiling for differences in risky health-related behaviours.Results: The QCA method suggested that the state of Tasmania may resemble South Australia in terms of having lower community inputs, as well as higher levels of mental health system inputs and interventions (such as prescriptions), than other states with the outcome of higher self-reported psychological distress. Theoretically, employment levels explained state-level differences in self-reported psychological distress. In terms of risky health-related behaviours, the QCA suggested that Tasmania leads other states in both socio-economic challenges and risky health behaviours. Theoretically, smoking explained state-level differences in self-assessed health. Conclusions: The QCA method has its weaknesses, but in this study, it allowed for the development of policy stories based on systematic comparisons of different states. It also suggested theoretically plausible explanations for differences in state-level outcomes.
机译:背景:标杆文献取得了重要进展,并提供了许多不同的人口健康指标,可用于比较各州的卫生系统。但是,仍然需要定性的,面向复杂性的方法,使决策者能够通过结合对政策解决方案有用的指标来制定解释性的“政策故事”。方法:在“现实世界,政策咨询”中试行了一种基于布尔方法的社会科学新的定性方法,即定性比较分析(QCA),以结合澳大利亚州级社区和卫生系统投入,干预措施和服务的指标人口健康结果。提供了针对特定慢性疾病领域(心理健康)的州输入和结果的分析,以及针对风险相关健康行为差异进行状态分析的结果。结果:QCA方法表明,塔斯马尼亚州的状态可能类似于南澳大利亚州自我报告的心理困扰较高的州比其他州的社区投入较低,以及精神卫生系统的投入和干预措施(例如处方药)水平较高。从理论上讲,就业水平解释了自我报告的心理困扰中国家水平的差异。在与风险健康相关的行为方面,QCA建议塔斯马尼亚州在社会经济挑战和风险健康行为方面领先于其他州。从理论上讲,吸烟可以解释自我评估健康状况的州级差异。结论:QCA方法有其缺点,但在本研究中,它允许根据不同国家的系统比较来制定政策案例。它还为州级结果的差异提出了理论上合理的解释。

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