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Evaluating the Impact of an Accountable Care Organization on Population Health: The Quasi-Experimental Design of the German Gesundes Kinzigtal

机译:评估责任医疗组织对人口健康的影响:德国Gesundes Kinzigtal的拟实验设计

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摘要

A central goal of accountable care organizations (ACOs) is to improve the health of their accountable population. No evidence currently links ACO development to improved population health. A major challenge to establishing the evidence base for the impact of ACOs on population health is the absence of a theoretically grounded, robust, operationally feasible, and meaningful research design. The authors present an evaluation study design, provide an empirical example, and discuss considerations for generating the evidence base for ACO implementation. A quasi-experimental study design using propensity score matching in combination with small-scale exact matching is implemented. Outcome indicators based on claims data were constructed and analyzed. Population health is measured by using a range of mortality indicators: mortality ratio, age at time of death, years of potential life lost/gained, and survival time. The application is assessed using longitudinal data from Gesundes Kinzigtal, one of the leading population-based ACOs in Germany. The proposed matching approach resulted in a balanced control of observable differences between the intervention (ACO) and control groups. The mortality indicators used indicate positive results. For example, 635.6 fewer years of potential life lost (2005.8 vs. 2641.4; t-test: sig. P < 0.05*) in the ACO intervention group (n = 5411) attributable to the ACO, also after controlling for a potential (indirect) immortal time bias by excluding the first half year after enrollment from the outcome measurement. This empirical example of the impact of a German ACO on population health can be extended to the evaluation of ACOs and other integrated delivery models of care.
机译:责任关怀组织(ACO)的中心目标是改善其责任人口的健康状况。目前尚无证据将ACO的发展与改善人口健康联系起来。建立ACO对人口健康影响的证据基础的主要挑战是缺乏理论上扎实,稳健,可操作且有意义的研究设计。作者提出了评估研究设计,提供了经验示例,并讨论了为ACO实施生成证据基础的注意事项。采用倾向得分匹配与小规模精确匹配相结合的准实验研究设计。构建并分析了基于索赔数据的结果指标。人口健康通过使用一系列死亡率指标来衡量:死亡率,死亡时的年龄,潜在生命丧失/获得的年限以及生存时间。该应用程序是使用来自德国领先的基于人口的ACO之一Gesundes Kinzigtal的纵向数据进行评估的。提议的匹配方法导致对干预组(ACO)和对照组之间可观察到的差异的平衡控制。使用的死亡率指标显示出积极的结果。例如,ACO干预组(n = 5411)的潜在生命损失减少了635.6年(2005.8 vs. 2641.4; t检验:s P. 0.05 *),也归因于ACO干预后(间接控制) )的不朽时间偏差,方法是将招生后的上半年从结果评估中排除。德国ACO对人口健康的影响的这个经验例子可以扩展到ACO和其他综合护理模式的评估。

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  • 来源
    《Population health management》 |2017年第3期|239-248|共10页
  • 作者单位

    Univ Calif Berkeley, Sch Publ Hlth, Hlth Policy & Management, 50 Univ Hall,7360, Berkeley, CA 94720 USA;

    Univ Witten Herdecke, Dept Hlth, Witten, Germany|OptiMedis AG, Hamburg, Germany;

    Hsch Neubrandenburg, Inst Hlth Econ & Hlth Care Management, Neubrandenburg, Germany;

    IESE Business Sch, Ctr Res Hlth Innovat Management, Barcelona, Spain;

    Berlin Univ Technol, Dept Hlth Care Management, Berlin, Germany;

    OptiMedis AG, Hamburg, Germany|London Sch Hyg & Trop Med, Dept Hlth Serv Res & Policy, London, England;

    Univ Calif Berkeley, Sch Publ Hlth, Hlth Policy & Management, 50 Univ Hall,7360, Berkeley, CA 94720 USA;

    OptiMedis AG, Hamburg, Germany|Gesundes Kinzigtal GmbH, Haslach, Germany;

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  • 正文语种 eng
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  • 入库时间 2022-08-18 03:47:06

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