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Background: Public reports that compare hospital mortality rates for patients with acute myocardial infarction are commonly used strategies for improving the quality of care delivered to these patients. Fair comparisons of hospital mortality rates require thorough adjustments for differences among patients in baseline mortality risk. This study examines the effect on hospital mortality rate comparisons of improved risk adjustment methods using diagnoses reported as present-at-admission., Methods and Results: Logistic regression models and related methods originally used by California to compare hospital mortality rates for patients with acute myocardial infarction are replicated. These results are contrasted with results obtained for the same hospitals by patient-level mortality risk adjustment models using present-at-admission diagnoses, using 3 statistical methods of identifying hospitals with higher or lower than expected mortality: indirect standardization, adjusted odds ratios, and hierarchical models. Models using present-at-admission diagnoses identified substantially fewer hospitals as outliers than did California model A for each of the 3 statistical methods considered., Conclusions: Large improvements in statistical performance can be achieved with the use of present-at-admission diagnoses to characterize baseline mortality risk. These improvements are important because models with better statistical performance identify different hospitals as having better or worse than expected mortality.

Objective: Hospital mortality outcomes for acute myocardial infarction (AMI) patients are a focus of quality improvement programs conducted by government agencies. AMI mortality risk-adjustment models using administrative data typically adjust for baseline differences in mortality risk with a limited set of common and definite comorbidities. In this study, we present an AMI mortality risk-adjustment model that adjusts for comorbid disease and for AMI severity using information from secondary diagnoses reported as present at admission for California hospital patients., Study Design and Setting: AMI patients were selected from California hospital administrative data for 1996 through 1999 according to criteria used by the California Hospital Outcomes Project Report on Heart Attack Outcomes, a state-mandated public report that compares hospital mortality outcomes. We compared results for the new model to two mortality risk-adjustment models used to assess hospital AMI mortality outcomes by the state of California, and to two other models used in prior research., Results: The model using present-at-admission diagnoses obtained substantially better discrimination between predicted survival and inpatient death than the other models we considered., Conclusion: AMI mortality risk-adjustment methods can be meaningfully improved using present-at-admission diagnoses to identify comorbid disease and conditions related closely to AMI.

Background: Racial and ethnic disparities in mortality have been demonstrated in several diseases. African Americans are hospitalized at a significantly higher rate than whites for aspiration pneumonia; however, no studies have investigated racial and ethnic disparities in mortality in this population., Objective: To assess the independent effect of race and ethnicity on in-hospital mortality among aspiration pneumonia discharges while comprehensively controlling for comorbid diseases, and to assess whether the prevalence and effects of comorbid illness differed across racial and ethnic categories., Design, Setting, and Participants: Retrospective cohort study of 41,581 patients admitted to California hospitals for aspiration pneumonia from 1996 through 1998, using principal and secondary diagnoses present on admission., Measurement: The primary outcome measure was in-hospital mortality., Results: The adjusted odds of in-hospital death for African-American compared with white discharges [odds ratio (OR)=1.01; 95% confidence interval (CI), 0.91-1.11] was not significantly different. The odds of death for Asian compared with white discharges was significantly lower (OR=0.83; 95% CI, 0.75-0.91). Hispanics had a significantly lower odds of death (OR=0.90; 95% CI, 0.82-0.988) compared to non-Hispanics. Comorbid diseases were more prevalent among African Americans and Asians than whites, and among Hispanics compared to non-Hispanics. Differences in effects of comorbid disease on mortality risk by race and ethnicity were not statistically significant., Conclusion: Asians have a lower risk of death, and the risk of death for African Americans is not significantly different from whites in this analysis of aspiration pneumonia discharges. Hispanics have a lower risk of death than non-Hispanics. While there are differences in prevalence of comorbid disease by racial and ethnic category, the effects of comorbid disease on mortality risk do not differ meaningfully by race or ethnicity.

Objective: To use diagnoses reported as present at admission in California hospital discharge abstract data to identify categories of comorbid disease and conditions related to aspiration pneumonia and to assess their association with hospital mortality., Study Design and Setting: The study population included all persons hospitalized in California from 1996 through 1999, with a principal diagnosis of aspiration pneumonia. Present at admission diagnoses representing comorbid diseases were separated from conditions closely related to aspiration pneumonia by a physician panel through a computer supported Delphi process. Multivariable logistic regression was used to assess the probability of hospital death after adjusting for these patient characteristics. The statistical performance of this method was compared to the performance of two independent methods for measuring comorbid disease. The practical significance of differences in statistical performance was assessed by comparing the estimated effects of age, race, and ethnicity after adjustments using each method., Results: Mortality risk adjustment using present at admission diagnoses resulted in substantially better statistical performance and in different measurements of the adjusted effects of age, race, and ethnicity., Conclusion: Reporting present at admission diagnoses in hospital discharge data yields meaningful improvements in hospital mortality risk adjustment.