Author: Berkowitz, Seth A; Traore, Carine Y; Singer, Daniel E; Atlas, Steven J
Title: Evaluating area-based socioeconomic status indicators for monitoring disparities within health care systems: results from a primary care network. Cord-id: gyaz5lvd Document date: 2015_1_1
ID: gyaz5lvd
Snippet: OBJECTIVE To determine which area-based socioeconomic status (SES) indicator is best suited to monitor health care disparities from a delivery system perspective. DATA SOURCES/STUDY SETTING 142,659 adults seen in a primary care network from January 1, 2009 to December 31, 2011. STUDY DESIGN Cross-sectional, comparing associations between area-based SES indicators and patient outcomes. DATA COLLECTION Address data were geocoded to construct area-based SES indicators at block group (BG), census tr
Document: OBJECTIVE To determine which area-based socioeconomic status (SES) indicator is best suited to monitor health care disparities from a delivery system perspective. DATA SOURCES/STUDY SETTING 142,659 adults seen in a primary care network from January 1, 2009 to December 31, 2011. STUDY DESIGN Cross-sectional, comparing associations between area-based SES indicators and patient outcomes. DATA COLLECTION Address data were geocoded to construct area-based SES indicators at block group (BG), census tract (CT), and ZIP code (ZIP) levels. Data on health outcomes were abstracted from electronic records. Relative indices of inequality (RIIs) were calculated to quantify disparities detected by area-based SES indicators and compared to RIIs from self-reported educational attainment. PRINCIPAL FINDINGS ZIP indicators had less missing data than BG or CT indicators (p < .0001). Area-based SES indicators were strongly associated with self-report educational attainment (p < .0001). ZIP, BG, and CT indicators all detected expected SES gradients in health outcomes similarly. Single-item, cut point defined indicators performed as well as multidimensional indices and quantile indicators. CONCLUSIONS Area-based SES indicators detected health outcome differences well and may be useful for monitoring disparities within health care systems. Our preferred indicator was ZIP-level median household income or percent poverty, using cut points.
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