期刊
POPULATION HEALTH METRICS
卷 13, 期 -, 页码 -出版社
BIOMED CENTRAL LTD
DOI: 10.1186/s12963-015-0044-2
关键词
Health rankings; Population health; Public health surveillance
资金
- Robert Wood Johnson Foundation [ID 71865]
Background: Annually since 2010, the University of Wisconsin Population Health Institute and the Robert Wood Johnson Foundation have produced the County Health Rankings-a population health checkup for the nation's over 3,000 counties. The purpose of this paper is to review the background and rationale for the Rankings, explain in detail the methods we use to create the health rankings in each state, and discuss the strengths and limitations associated with ranking the health of communities. Methods: We base the Rankings on a conceptual model of population health that includes both health outcomes (mortality and morbidity) and health factors (health behaviors, clinical care, social and economic factors, and the physical environment). Data for over 30 measures available at the county level are assembled from a number of national sources. Z-scores are calculated for each measure, multiplied by their assigned weights, and summed to create composite measure scores. Composite scores are then ordered and counties are ranked from best to worst health within each state. Results: Health outcomes and related health factors vary significantly within states, with over two-fold differences between the least healthy counties versus the healthiest counties for measures such as premature mortality, teen birth rates, and percent of children living in poverty. Ranking within each state depicts disparities that are not apparent when counties are ranked across the entire nation. Discussion: The County Health Rankings can be used to clearly demonstrate differences in health by place, raise awareness of the many factors that influence health, and stimulate community health improvement efforts. The Rankings draws upon the human instinct to compete by facilitating comparisons between neighboring or peer counties within states. Since no population health model, or rankings based off such models, will ever perfectly describe the health of its population, we encourage users to look to local sources of data to understand more about the health of their community.
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