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Thursday, January 11
Thu, Jan 11, 11:00 AM - 12:45 PM
Crystal Ballroom A
Rural Health

Measuring need using population health indicators: Composite methods shortchange rural counties (304260)

*Charity B Breneman, South Carolina Rural Health Research Center 
Jan Marie Eberth, University of South Carolina 
Janice C Probst, University of South Carolina 

Keywords: rural, population need

Recent work has noted differences in population health indicators, assessed at the county level. Complex metrics may not perform well for rural counties. We compared three metrics for assessing population need: age-adjusted all-cause mortality (ACM), years of potential life lost (YPLL), and County Health Rankings (CHR). For CHR, individual county-level data were rescaled using z-scores based on national values prior to calculating a weighted composite score. Z-scores were truncated to +/- 3.0 in order to eliminate outliers. We compared the 10 rural counties with the poorest outcomes identified by the three metrics. Of the 5 measures used in CHR, 2 had missing data for 5-9% of the counties. About 9% of the rural counties were missing data for YPLL. Differences were found in the rankings of rural counties. High levels of missing data and the use of imputed data make some common metrics of community need unsuitable for rural counties.