Key result
Adding socioeconomic status to standard risk-adjustment models for 30-day acute myocardial infarction mortality had a negligible effect on hospital profiling (median absolute difference 0.1%).
Why the study?
Does adding socioeconomic status to standard risk-adjustment models change hospital-specific 30-day mortality rates for acute myocardial infarction?
Observational
Yes
Does adding socioeconomic status to standard risk-adjustment models change hospital-specific 30-day mortality rates for acute myocardial infarction?
Adding socioeconomic status to standard risk-adjustment models for acute myocardial infarction hospital profiling has a negligible effect on hospital-specific mortality rates.
BACKGROUND: Critics of "scorecard medicine" often highlight the incompleteness of risk-adjustment methods used when accounting for baseline patient differences. Although socioeconomic status is a highly important determinant of adverse outcome for patients admitted to the hospital with acute myocardial infarction, it has not been used in most risk-adjustment models for cardiovascular report cards. OBJECTIVES: To determine the incremental impact of socioeconomic status adjustments on age, sex, and illness severity for hospital-specific 30-day mortality rates after acute myocardial infarction. METHODS: The authors compared the absolute and relative hospital-specific 30-day acute myocardial infarction mortality rates in 169 hospitals throughout Ontario between April 1, 1994 and March 31, 1997. Patient socioeconomic status was characterized by median neighborhood income using postal codes and 1996 Canadian census data. They examined two risk-adjustment models: the first adjusted for age, sex, and illness severity (standard), whereas the second adjusted for age, sex, illness severity, and median neighborhood income level (socioeconomic status). RESULTS: There was an extremely strong correlation between 'standard' and 'socioeconomic status' risk-adjusted mortality rates (r = 0.99). Absolute differences in 30-day risk-adjusted mortality rates between the socioeconomic status and standard risk-adjustment models were small (median, 0.1%; 25th-75th percentile, 0.1-0.2). The agreement in the quintile rankings of hospitals between the socioeconomic status and standard risk-adjustment models was high (weighted kappa = 0.93). CONCLUSION: Despite its importance as a determinant of patient outcomes, the effect of socioeconomic status on hospital-specific mortality rates over and above standard risk-adjustment methods for acute myocardial infarction hospital profiling in Ontario was negligible.
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Alter et al. (2002) conducted an observational in acute myocardial infarction. Socioeconomic status risk-adjustment model vs. Standard risk-adjustment model was evaluated on Hospital-specific 30-day mortality rates (r = 0.99). Adding socioeconomic status to standard risk-adjustment models for 30-day acute myocardial infarction mortality had a negligible effect on hospital profiling (median absolute difference 0.1%).
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