ABSTRACT [FROM JOURNAL]
Objectives: We 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 non‐white, Hispanic, or poor patients.
Methods: We performed a cross‐sectional analysis 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 non‐white 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.
Results: The overall mortality rate among 170,750 inpatients was 6.9%. Mortality was significantly higher for non‐white and Hispanic patients (adjusted odds ratio [aOR] 1.27, 95%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 which moved out of the lowest‐performing decile, relative to other hospitals, had significantly more non‐white and Hispanic patients (68% vs. 11%, P<0.001) and poor patients (56% vs. 10%, P<0.001).
Conclusions: Sociodemographic risk‐adjustment of emergency care sensitive mortality improves apparent performance of some hospitals treating a large number of non‐white, Hispanic, or poor patients. This may help these hospitals avoid financial penalties in pay‐for‐performance programs.