The impact of clinical vs administrative claims coding on hospital risk‐adjusted outcomes

Background Comorbid condition and hospital risk‐adjusted outcomes prevalence were compared based on clinical registry vs administrative claims data. Hypothesis Risk‐adjusted outcomes will vary depending on the source of comorbidity data used. Methods Clinical data from hospitalized Can Rapid Risk Stratification of Unstable Angina Patients Suppress Adverse Outcomes with Early Implementation of the American College of Cardiology/American Heart Association (ACC/AHA) Guidelines (CRUSADE) non‐ST‐segment elevation myocardial infarction (NSTEMI) patients ≥65 years was linked to Medicare claims. Eight common comorbid conditions were coded and compared between registry data (derived from medical record review) and claims data; hospital‐level observed vs expected ratios and outlier status for 30‐day readmission and mortality were calculated using logistic generalized estimating equations for clinical vs claims data. Results Of 68 199 NSTEMI patients, 48.1% were female, 86.9% were white, and median age was 78. Degree of agreement between data sources for comorbid condition prevalence was 67.8% for myocardial infarction and 89.3% for diabetes. Overall, multivariable model performance was similar: Medicare mortality c‐statistics is 0.69 vs CRUSADE is 0.71; readmission c‐statistics is 0.59 for both. Hospital ratings were similar regardless of data source (mortality, R 2 = 0.97863; readmission, R 2 = 0.97858). Eighty‐two hospitals were mortality outliers in claims‐based models; of these, 70 were outliers in registry‐based models. Forty‐five hospitals were readmission outliers in claims‐based models; of these, 39 were outliers in registry‐based models. Conclusions There were significant differences in individual comorbid condition prevalence when derived from registries vs claims, but hospital‐level outcomes were comparable.