Objective: To develop and validate a claims-based comorbidity score for patients undergoing major surgery, and compare its performance with established comorbidity scores.
Data source: Five percent Medicare data from 2007 to 2014.
Study design: Retrospective cohort study of patients aged ≥65 years undergoing six major operations (N = 99 250).
Data collection: One-year mortality was the primary outcome. Secondary outcomes were hospital mortality, 30-day mortality, 30-day readmission, and length of stay. The comorbidity score was developed in the derivation cohort (70 percent sample) using logistic regression model. The comorbidity score was calibrated and validated in the validation cohort (30 percent sample), and compared against the Charlson, Elixhauser, and Centers for Medicare and Medicaid Services Hierarchical Condition Categories (CMS-HCC) comorbidity scores using c-statistic, net reclassification improvement, and integrated discrimination improvement.
Principal findings: In the validation cohort, the surgery-specific comorbidity score was well calibrated and performed better than the Charlson, Elixhauser, and CMS-HCC comorbidity scores for all outcomes; the performance was comparable to the CMS-HCC for 30-day readmission. For example, the surgery-specific comorbidity score (c-statistic = 0.792; 95% CI, 0.785-0.799) had greater discrimination than the Charlson (c-statistic = 0.747; 95% CI, 0.739-0.755), Elixhauser (c-statistic = 0.747; 95% CI, 0.735-0.755), or CMS-HCC (c-statistic = 0.755; 95% CI, 0.747-0.763) scores in predicting 1-year mortality. The net reclassification improvement and integrated discrimination improvement were greater for surgery-specific comorbidity score compared to the Charlson, Elixhauser, and CMS-HCC scores.
Conclusions: Compared to commonly used comorbidity measures, a surgery-specific comorbidity score better predicted outcomes in the surgical population.
Keywords: comorbidity score; confounding; risk adjustment; surgery.
© Health Research and Educational Trust.