3.8 Article

Predictors of Readmission after Inpatient Plastic Surgery

期刊

ARCHIVES OF PLASTIC SURGERY-APS
卷 41, 期 2, 页码 116-121

出版社

KOREAN SOC PLASTIC & RECONSTRUCTIVE SURGERY
DOI: 10.5999/aps.2014.41.2.116

关键词

Inpatients; Surgery, plastic; Patient readmission

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资金

  1. Vanderbilt University School of Medicine
  2. NIH CTSA Grant [UL1RR024975]

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Background Understanding risk factors that increase readmission rates may help enhance patient education and set system-wide expectations. We aimed to provide benchmark data on causes and predictors of readmi-ssion following inpatient plastic surgery. Methods The 2011 National Surgical Quality Improvement Program dataset was reviewed for patients with both Plastics as their recorded surgical specialty and inpatient status. Readmission was tracked through the Unplanned Readmission variable. Patient characteristics and outcomes were compared using chi-squared analysis and Student's t-tests for categorical and continuous variables, respectively. Multivariate regression analysis was used for identifying predictors of readmission. Results A total of 3,671 inpatient plastic surgery patients were included. The unplanned readmission rate was 7.11%. Multivariate regression analysis revealed a history of chronic obstructive pulmonary disease (COPD) (odds ratio [OR], 2.01; confidence interval [CI], 1.12-3.60; P=0.020), previous percutaneous coronary intervention (PCI) (OR, 2.69; CI, 1.21-5.97; P=0.015), hypertension requiring medication (OR, 1.65; CI, 1.22-2.24; P<0.001), bleeding disorders (OR, 1.70; CI, 1.01-2.87; P=0.046), American Society of Anesthesiologists (ASA) class 3 or 4 (OR, 1.57; CI, 1.15-2.15; P=0.004), and obesity (body mass index >= 30) (OR, 1.43; CI, 1.09-1.88, P=0.011) to be significant predictors of readmission. Conclusions Inpatient plastic surgery has an associated 7.11% unplanned readmission rate. History of COPD, previous PCI, hypertension, ASA class 3 or 4, bleeding disorders, and obesity all proved to be significant risk factors for readmission. These findings will help to benchmark inpatient readmission rates and manage patient and hospital system expectations.

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