Article ID Journal Published Year Pages File Type
515367 Healthcare 2016 6 Pages PDF
Abstract

BackgroundGeographic variation in healthcare has been traditionally studied in large areas such as hospital referral regions or service areas. These analyses are limited by variation that exists within local communities.Materials and methodsUsing a New York claims database, we analyzed variation in emergency department use using 35 million visits from 2008 to 2012 among 4797 Census tracts, a smaller unit than usually studied. Using multivariate analysis, we studied associations between population characteristics and proximity to healthcare with rates of emergency department use. We analyzed how factors associated with emergency department utilization differed among urban, suburban, and rural regions.ResultsWe found significant geographic variation in emergency department use among Census tracts. Public insurance and uninsurance were correlated with high emergency department utilization across all types of regions. We found that race, ethnicity, and poverty were only associated with high emergency department use in urban regions. In suburban and rural regions, a lower proportion of elderly residents and shorter distances to the nearest ED were correlated with high emergency department use.ConclusionsSignificant variation in emergency department use exists locally when studied within small geographic areas. Insurance type is significantly associated with variation in emergency department use across urban, suburban, and rural regions, whereas the significance of other factors depended on urbanicity.ImplicationsStudying geographic variation at a more granular level can lead to better understanding of local population health, drivers of healthcare utilization, and inform targeted interventions. Given heterogeneity in emergency department use by Census tract, policies directed at shaping acute care utilization must consider these local geographic differences.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science Applications
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