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Data-driven decision making in the prevention of substance related harm: Results from the Strategic Prevention Framework State Incentive Grant Program

机译:预防物质相关损害的数据驱动决策:《战略预防框架国家奖励计划》的结果

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The Strategic Prevention Framework State Incentive Grant Program (SPF SIG) is a national public-health initiative in the United States to prevent and reduce substance-related harm. The model promotes data-driven decision making (DDDM), with an emphasis on using epidemiological data to help select prevention priorities and to allocate prevention resources. This article examines how well the first two cohorts of SPF SIG states (N = 26) implemented DDDM, and also explores what factors facilitated and hindered the process. Data were collected by reviewing and coding states' strategic plans, supplemented by interviews with state project directors, evaluators, and epidemiological workgroup chairs. Fidelity to the process was scored as high, medium, or low, based on transparency and support from relevant evidence. On selecting prevention priorities, 81% of states received high or medium scores on all priorities selected. On allocating prevention resources, 85% received a high or medium score. Facilitators included collaboration among stakeholders, training and technical assistance, and efforts of epidemiological workgroups and evaluators. However, states that lacked established data infrastructures for prevention were at a decided disadvantage in implementing the model. Future implications for SPF SIG states and ongoing challenges to DDDM in general are discussed.
机译:战略预防框架国家奖励拨款计划(SPF SIG)是美国的一项国家公共卫生计划,旨在预防和减少与物质有关的伤害。该模型促进以数据为依据的决策(DDDM),重点是使用流行病学数据来帮助选择预防重点和分配预防资源。本文研究了SPF SIG的前两个队列状态(N = 26)实施DDDM的情况,并探讨了哪些因素促进和阻碍了该过程。通过审查和编码州的战略计划来收集数据,并与州项目负责人,评估人员和流行病学工作组主席进行访谈。基于透明度和相关证据的支持,对流程的忠诚度被评为高,中或低。在选择预防优先事项时,有81%的州在所有选定优先事项上得分都很高或中等。在分配预防资源方面,有85%的学生获得了高分或中分。主持人包括利益相关者之间的合作,培训和技术援助以及流行病学工作组和评估人员的努力。但是,缺乏建立预防数据基础设施的州在实施该模型时处于明显的劣势。讨论了对SPF SIG状态的未来影响以及对DDDM的持续挑战。

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