Background: Coronary artery bypass graft (CABG) operations are associated with all-cause readmission rates of approximately 15%. In attempts to reduce readmission rates, the Hospital Readmission Reduction Program expanded to include CABG operations in 2015. The aim of this study was therefore to develop a predictive readmission scale that would identify patients at higher risk of readmission after CABG using commonly available administrative data. Methods: Data of 126,519 patients from California and New York (derivation cohort) and 94,318 patients from Florida and Washington (validation cohort) were abstracted from the State Inpatient Database (2006 to 2011). The readmission after CABG scale was developed to predict 30-day readmission risk and was validated against a separate cohort. Results: Thirty-day CABG readmission rates were 23% in the derivation cohort and 21% in the validation cohort. Predictive factors included older age, female gender (odds ratio [OR], 1.34), African American ethnicity (OR, 1.13), Medicare or Medicaid insurance, and comorbidities, including renal failure (OR, 1.56) and congestive heart failure (OR, 2.82). These were independently predictive of increased readmission rates (p < 0.01). The readmission scale was then created with these preoperative factors. When applied to the validation cohort, it explained 98% of the readmission variability. Conclusions: The readmission after CABG scale reliably predicts a patient's 30-day CABG readmission risk. By identifying patients at high-risk for readmission before their procedure, risk reduction strategies can be implemented to reduce readmissions and healthcare expenditures.
All Science Journal Classification (ASJC) codes
- Pulmonary and Respiratory Medicine
- Cardiology and Cardiovascular Medicine