Derivation and validation of a diagnostic score based on case-mix groups to predict 30-day death or urgent readmission

BACKGROUND Between 5% and 10% of patients die or are urgently readmitted within 30 days of discharge from hospital. Readmission risk indexes have either excluded acute diagnoses or modelled them as multiple distinct variables. In this study, we derived and validated a score summarizing the influence of acute hospital diagnoses and procedures on death or urgent readmission within 30 days. METHODS From population-based hospital abstracts in Ontario, we randomly sampled 200 000 discharges between April 2003 and March 2009 and determined who had been readmitted urgently or died within 30 days of discharge. We used generalized estimating equation modelling, with a sample of 100 000 patients, to measure the adjusted association of various case-mix groups (CMGs-homogenous groups of acute care inpatients with similar clinical and resource-utilization characteristics) with 30-day death or urgent readmission. This final model was transformed into a scoring system that was validated in the remaining 100 000 patients. RESULTS Patients in the derivation set belonged to 1 of 506 CMGs and had a 6.8% risk of 30-day death or urgent readmission. Forty-seven CMG codes (more than half of which were directly related to chronic diseases) were independently associated with this outcome, which led to a CMG score that ranged from -6 to 7 points. The CMG score was significantly associated with 30-day death or urgent readmission (unadjusted odds ratio for a 1-point increase in CMG score 1.52, 95% confidence interval [CI] 1.49-1.56). Alone, the CMG score was only moderately discriminative (C statistic 0.650, 95% CI 0.644-0.656). However, when the CMG score was added to a validated risk index for death or readmission, the C statistic increased to 0.759 (95% CI 0.753-0.765). The CMG score was well calibrated for 30-day death or readmission. INTERPRETATION In this study, we developed a scoring system for acute hospital diagnoses and procedures that could be used as part of a risk-adjustment methodology for analyses of postdischarge outcomes.