• IoannidesKimon L HKLHDepartment of Emergency Medicine, Temple University Hospital, Philadelphia, PA.Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA., Avi Baehr, David N Karp, Douglas J Wiebe, Brendan G Carr, Daniel N Holena, and M Kit Delgado.
• Department of Emergency Medicine, Temple University Hospital, Philadelphia, PA.
• Acad Emerg Med. 2018 Aug 1; 25 (8): 856869856-869.

ObjectivesWe determined the impact of including race, ethnicity, and poverty in risk adjustment models for emergency care-sensitive conditions mortality that could be used for hospital pay-for-performance initiatives. We hypothesized that adjusting for race, ethnicity, and poverty would bolster rankings for hospitals that cared for a disproportionate share of nonwhite, Hispanic, or poor patients.MethodsWe performed a cross-sectional analysis of patients admitted from the emergency department to 157 hospitals in Pennsylvania with trauma, sepsis, stroke, cardiac arrest, and ST-elevation myocardial infarction. We used multivariable logistic regression models to predict in-hospital mortality. We determined the predictive accuracy of adding patient race and ethnicity (dichotomized as non-Hispanic white vs. all other Hispanic or nonwhite patients) and poverty (uninsured, on Medicaid, or lowest income quartile zip code vs. all others) to other patient-level covariates. We then ranked each hospital on observed-to-expected mortality, with and without race, ethnicity, and poverty in the model, and examined characteristics of hospitals with large changes between models.ResultsThe overall mortality rate among 170,750 inpatients was 6.9%. Mortality was significantly higher for nonwhite and Hispanic patients (adjusted odds ratio [aOR] = 1.27, 95% confidence interval [CI] = 1.19-1.36) and poor patients (aOR = 1.21, 95% CI = 1.12-1.31). Adding race, ethnicity, and poverty to the risk adjustment model resulted in a small increase in C-statistic (0.8260 to 0.8265, p = 0.002). No hospitals moved into or out of the highest-performing decile when adjustment for race, ethnicity, and poverty was added, but the three hospitals that moved out of the lowest-performing decile, relative to other hospitals, had significantly more nonwhite and Hispanic patients (68% vs. 11%, p < 0.001) and poor patients (56% vs. 10%, p < 0.001).ConclusionsSociodemographic risk adjustment of emergency care-sensitive mortality improves apparent performance of some hospitals treating a large number of nonwhite, Hispanic, or poor patients. This may help these hospitals avoid financial penalties in pay-for-performance programs.© 2018 by the Society for Academic Emergency Medicine.

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