Making Better Use of Population Health Data for Community Health Needs Assessments.

Michael A Stoto, Mary V Davis, Abby Atkins
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引用次数: 7

Abstract

Research objective: Non-profit hospitals are required to work with community organizations to prepare a Community Health Needs Assessment (CHNA) and implementation strategy (IS). In concert with the health care delivery system's transformation from volume to value and efforts to enhance multi-sector collaboration, such community health improvement (CHI) processes have the potential to bridge efforts of the health care delivery sector, public health agencies, and community organizations to improve population health. Having a shared measurement system is critical to achieving collective impact, yet despite the availability of community-level data from a variety of sources, many CHI processes lack clear, measurable objectives and evaluation plans. Through an in-depth analysis of ten exemplary CHI processes, we sought to identify best practices for population health measurement with a focus on measures for needs assessments and priority setting.

Study design: Based on a review of the scientific literature, professional publications and presentations, and nominations from a national advisory panel, we identified 10 exemplary CHI processes. Criteria of choice were whether (1) the CHIs articulate a clear definition of intended outcomes; (2) clear, focused, measurable objectives and expected outcomes, including health equity; (3) expected outcomes are realistic and addressed with specific action plans; and (4) whether the plans and their associated performance measures become fully integrated into agencies and become a way of being for the agencies. We then conducted an in-depth analysis of CHNA, IS, and related documents created by health departments and leading hospitals in each process.

Population studied: U.S. hospitals.

Principal findings: Census, American Community Survey, and similar data are available for smaller areas are used to describe the populations covered, and, to a lesser extent, to identify health issues where there are disparities and inequities.Common data sources for population health profiles, including risk factors and population health outcomes, are vital statistics, survey data including BRFSS, infectious disease surveillance data, hospital & ED data, and registries. These data are typically available only at the county level, and only occasionally are broken down by race, ethnicity, age, poverty.There is more variability in format and content of ISs than CHNAs; the most developed models include population-level goals/objectives and strategies with clear accountability and metrics. Other hospital IS's are less developed.

Conclusions: The county is the unit of choice because most population health profile data are not available for sub-county areas, but when a hospital serves a population more broadly or narrowly defined, appropriate data are not available to set priorities or monitor progress.Measure definitions are taken from the original data sources, so comparisons across measures is difficult. Thus, although CHNAs cover many of the same topics, the measures used vary markedly. Using the same community health profile, e.g. County Health Rankings, would simplify benchmarking and trend analysis.Implications for Policy or Practice: It is important to develop population health data that can be disaggregated to the appropriate geographical level and to groups defined by race and ethnicity, socioeconomic status, and other factors associated with health outcomes.

Abstract Image

更好地利用人口健康数据进行社区卫生需求评估。
研究目标:非营利性医院需要与社区组织合作,制定社区卫生需求评估(CHNA)和实施战略(IS)。随着医疗保健提供系统从数量到价值的转变以及加强多部门合作的努力,这种社区健康改善(CHI)过程有可能弥合医疗保健提供部门、公共卫生机构和社区组织改善人口健康的努力。拥有一个共享的衡量系统对于实现集体影响至关重要,然而,尽管可以从各种来源获得社区层面的数据,但许多CHI过程缺乏明确、可衡量的目标和评估计划。通过对十个典型的CHI过程的深入分析,我们试图确定人口健康测量的最佳实践,重点是需求评估和优先事项设定的措施。研究设计:根据对科学文献、专业出版物和演示以及国家咨询小组的提名的审查,我们确定了10个典型的CHI过程。选择的标准是:(1)CHI是否明确定义了预期结果;(2) 明确、重点突出、可衡量的目标和预期成果,包括卫生公平;(3) 预期结果是现实的,并通过具体的行动计划加以解决;以及(4)计划及其相关绩效衡量标准是否完全融入各机构,并成为各机构的一种存在方式。然后,我们对CHNA、IS以及卫生部门和领先医院在每个过程中创建的相关文件进行了深入分析。研究人群:美国医院。主要发现:人口普查、美国社区调查和较小地区的类似数据用于描述覆盖的人口,并在较小程度上用于确定存在差异和不平等的健康问题。人口健康状况的常见数据来源,包括风险因素和人口健康结果,包括生命统计、包括BRFSS在内的调查数据、传染病监测数据、医院和急诊数据以及登记册。这些数据通常只在县一级提供,偶尔也会按种族、民族、年龄和贫困程度进行细分。is的格式和内容比CHNA有更多的可变性;最发达的模型包括人口层面的目标/目的和具有明确问责制和衡量标准的战略。其他医院的IS则不太发达。结论:县是选择的单位,因为大多数人口健康状况数据都不适用于县以下地区,但当医院为更广泛或狭义的人群提供服务时,就无法获得适当的数据来设定优先事项或监测进展。度量定义取自原始数据源,因此很难在度量之间进行比较。因此,尽管CHNA涵盖了许多相同的主题,但所使用的措施差异很大。使用相同的社区健康状况,例如县健康排名,将简化基准测试和趋势分析。对政策或实践的影响:重要的是要制定人口健康数据,这些数据可以分解到适当的地理水平,并根据种族和民族、社会经济地位和其他与健康结果相关的因素来定义群体。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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