ArticleAcademic emergency medicine : official journal of the Society for Academic Emergency Medicine2018
Measuring Emergency Care Survival: The Implications of Risk Adjusting for Race and Poverty.
Article in Academic emergency medicine : official journal of the Society for Academic Emergency Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Socioeconomic disadvantage is a leading variable in risk score for major amputation following emergent infrainguinal arterial bypass surgery.Journal of vascular surgery · 2024Article
- Association of Medicare-Medicaid Dual Eligibility and Race and Ethnicity With Ischemic Stroke Severity.JAMA network open · 2022Article
- Testing of a Risk-Standardized Complication Rate Electronic Clinical Quality Measure (eCQM) for Total Hip and/or Total Knee Arthroplasty.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Toward Structural Competency in Emergency Medical Education.AEM education and training · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
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.
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