Zubin J Eapen1, Lisa A McCoy2, Gregg C Fonarow2, Clyde W Yancy2, Marie Lynn Miranda2, Eric D Peterson2, Robert M Califf2, Adrian F Hernandez2. 1. From the Duke Clinical Research Institute, Durham, NC (Z.J.E., L.A.M., E.D.P., R.M.C., A.F.H.); Division of Cardiology, Ronald Reagan-UCLA Medical Center, Ahmanson-UCLA Cardiomyopathy Center, Los Angeles, CA (G.C.F.); Division of Cardiology, Northwestern University Medical Center, Chicago, IL (C.W.Y.); and Departments of Pediatrics and Obstetrics and Gynecology, School of Natural Resources and Environment, University of Michigan, Ann Arbor (M.L.M.). zubin.eapen@duke.edu. 2. From the Duke Clinical Research Institute, Durham, NC (Z.J.E., L.A.M., E.D.P., R.M.C., A.F.H.); Division of Cardiology, Ronald Reagan-UCLA Medical Center, Ahmanson-UCLA Cardiomyopathy Center, Los Angeles, CA (G.C.F.); Division of Cardiology, Northwestern University Medical Center, Chicago, IL (C.W.Y.); and Departments of Pediatrics and Obstetrics and Gynecology, School of Natural Resources and Environment, University of Michigan, Ann Arbor (M.L.M.).
Abstract
BACKGROUND: An individual's socioeconomic status (SES) is associated with health outcomes and mortality, yet it is unknown whether accounting for SES can improve risk-adjustment models for 30-day outcomes among Centers for Medicare & Medicaid Services beneficiaries hospitalized with heart failure. METHODS AND RESULTS: We linked clinical data on hospitalized patients with heart failure in the Get With The Guidelines-Heart Failure database (January 2005 to December 2011) with Centers for Medicare & Medicaid Services claims and county-level SES data from the 2012 Area Health Resources Files. We compared the discriminatory capabilities of multivariable models that adjusted for SES, patient, and hospital characteristics to determine whether county-level SES data improved prediction or changed hospital rankings for 30-day all-cause mortality and rehospitalization. After adjusting for patient and hospital characteristics, median household income (per $5000 increase) was inversely associated with odds of 30-day mortality (odds ratio, 0.97; 95% confidence interval, 0.95-1.00; P=0.032) and the percentage of people with at least a high school diploma (per 5 U increase) was associated with lower odds of 30-day rehospitalization (odds ratio, 0.95; 95% confidence interval, 0.91-0.99). After adjustment for county-level SES data, relative to whites, Hispanic ethnicity (odds ratio, 0.70; 95% confidence interval, 0.58-0.83) and black race (odds ratio, 0.57; 95% confidence interval, 0.50-0.65) remained significantly associated with lower 30-day mortality, but had similar 30-day rehospitalization. County-level SES did not improve risk adjustment or change hospital rankings for 30-day mortality or rehospitalization. CONCLUSIONS: County-level SES data are modestly associated with 30-day outcomes for Centers for Medicare & Medicaid Services beneficiaries hospitalized with heart failure, but do not improve risk adjustment models based on patient characteristics alone.
BACKGROUND: An individual's socioeconomic status (SES) is associated with health outcomes and mortality, yet it is unknown whether accounting for SES can improve risk-adjustment models for 30-day outcomes among Centers for Medicare & Medicaid Services beneficiaries hospitalized with heart failure. METHODS AND RESULTS: We linked clinical data on hospitalized patients with heart failure in the Get With The Guidelines-Heart Failure database (January 2005 to December 2011) with Centers for Medicare & Medicaid Services claims and county-level SES data from the 2012 Area Health Resources Files. We compared the discriminatory capabilities of multivariable models that adjusted for SES, patient, and hospital characteristics to determine whether county-level SES data improved prediction or changed hospital rankings for 30-day all-cause mortality and rehospitalization. After adjusting for patient and hospital characteristics, median household income (per $5000 increase) was inversely associated with odds of 30-day mortality (odds ratio, 0.97; 95% confidence interval, 0.95-1.00; P=0.032) and the percentage of people with at least a high school diploma (per 5 U increase) was associated with lower odds of 30-day rehospitalization (odds ratio, 0.95; 95% confidence interval, 0.91-0.99). After adjustment for county-level SES data, relative to whites, Hispanic ethnicity (odds ratio, 0.70; 95% confidence interval, 0.58-0.83) and black race (odds ratio, 0.57; 95% confidence interval, 0.50-0.65) remained significantly associated with lower 30-day mortality, but had similar 30-day rehospitalization. County-level SES did not improve risk adjustment or change hospital rankings for 30-day mortality or rehospitalization. CONCLUSIONS: County-level SES data are modestly associated with 30-day outcomes for Centers for Medicare & Medicaid Services beneficiaries hospitalized with heart failure, but do not improve risk adjustment models based on patient characteristics alone.
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