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Unplanned readmissions following breast cancer surgery.
American Journal of Surgery 2019 November
BACKGROUND: Understanding the underlying factors associated with unplanned readmissions is an important first step toward interventions designed to improve quality of care. This study aimed to identify predictors of unplanned 30-day readmission using a national breast surgery cohort.
STUDY DESIGN: Using the National Cancer Database, we performed a review of patients undergoing surgery for breast cancer from 2006 to 2014. A multivariatble logistic regression model was generated to assess predictors of 30-day unplanned readmission.
RESULTS: Of 944,092 patients identified, 15,695 (1.7%) had an unplanned readmission within 30 days. Significant predictors of readmission included: increased procedure complexity, high co-morbidity score, Medicaid or lack of insurance, and low annual hospital volume; p < 0.0001.
CONCLUSION: Unplanned readmission following breast surgery is an uncommon event. However, our results demonstrate risk factors associated with higher rates of readmission following surgery. Understanding the underlying causes for readmission allows for identification of high-risk individuals and the design of targeted intervention programs.
STUDY DESIGN: Using the National Cancer Database, we performed a review of patients undergoing surgery for breast cancer from 2006 to 2014. A multivariatble logistic regression model was generated to assess predictors of 30-day unplanned readmission.
RESULTS: Of 944,092 patients identified, 15,695 (1.7%) had an unplanned readmission within 30 days. Significant predictors of readmission included: increased procedure complexity, high co-morbidity score, Medicaid or lack of insurance, and low annual hospital volume; p < 0.0001.
CONCLUSION: Unplanned readmission following breast surgery is an uncommon event. However, our results demonstrate risk factors associated with higher rates of readmission following surgery. Understanding the underlying causes for readmission allows for identification of high-risk individuals and the design of targeted intervention programs.
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