Preoperative Scale to Determine All-Cause Readmission After Coronary Artery Bypass Operations
Aleksander Zywot1, Christine S M Lau2, Nina Glass3
1Department of Surgery, Morristown Medical Center, Morristown, New Jersey.
Insights
A new scale predicts 30-day readmission risk after coronary artery bypass graft (CABG) surgery. Identifying high-risk patients allows for targeted interventions to reduce readmissions and healthcare costs.
Area of Science:
- Cardiovascular Surgery
- Health Services Research
- Predictive Analytics
Background:
- Coronary artery bypass graft (CABG) operations have high readmission rates, prompting initiatives like the Hospital Readmission Reduction Program.
- Reducing 30-day readmissions post-CABG is a key healthcare quality metric.
Purpose of the Study:
- To develop and validate a predictive scale for 30-day readmission risk following CABG.
- To utilize readily available administrative data for risk stratification.
Main Methods:
- Development of a readmission scale using administrative data from 126,519 CABG patients (California, New York).
- Validation of the scale on a separate cohort of 94,318 CABG patients (Florida, Washington).
- Analysis of preoperative factors associated with 30-day readmission.
Main Results:
- Identified key predictors of readmission: older age, female gender, African American ethnicity, Medicare/Medicaid insurance, renal failure, and congestive heart failure.
- The developed scale demonstrated high predictive power, explaining 98% of readmission variability in the validation cohort.
- Observed 30-day readmission rates of 23% (derivation) and 21% (validation).
Conclusions:
- The 'readmission after CABG' scale reliably predicts 30-day readmission risk.
- Preoperative identification of high-risk patients enables targeted interventions.
- Implementation of this scale can reduce readmissions and associated healthcare expenditures.
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.
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