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Identifying Risk Factors Leading to Unanticipated Postoperative Readmission. | LitMetric

Identifying Risk Factors Leading to Unanticipated Postoperative Readmission.

Ann Plast Surg

From the *Division of Plastic and Reconstructive Surgery, Department of Surgery, and †University of Florida College of Medicine, Gainesville, FL.

Published: June 2017

Introduction: Unanticipated postoperative readmissions are a grading metric directly linked to both the quality of patient care and physician reimbursement. However, little data exist to define factors responsible for these readmissions in the plastic surgery patient population. This study aims to identify patient risk factors contributing to unanticipated postoperative readmissions to optimize perioperative patient care and mitigate negative financial impact upon providers.

Methods: We present an institutional review board-approved study retrospective review of 819 plastic surgery patients undergoing operative procedures performed at our institution between January 1, 2013, and December 31, 2014. All unanticipated readmissions within 30 days of an operation were identified and subjected to statistical analysis in an effort to determine whether these readmissions were associated with identifiable patient risk factors.

Results: One hundred forty-nine (18.1%) of the 819 investigated patients underwent readmission, reoperation, or both within 30 postoperative days. Seventy-four (9%) patients required hospital readmission, alone; 55 (6.7%) underwent readmission with operative intervention; and 20 (2.4%) required outpatient operative intervention without readmission. Readmitted patients were significantly more likely to have a positive smoking history (P = 0.009), hypertension (P = 0.0008), congestive heart failure (P = 0.0015), chronic obstructive pulmonary disease (P = 0.023), a higher mean age (P = 0.0001), and a higher Charlson Comorbidity Score (P = 0.0001).

Conclusions: These results identify risk factors associated with unanticipated postoperative readmissions specific to a plastic surgery patient population. With this information, practitioners can allocate appropriate perioperative resources and planning for patients at increased risk for readmission, thereby improving delivery of patient care and satisfying quality metrics linked to practitioner reimbursement.

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Source
http://dx.doi.org/10.1097/SAP.0000000000001061DOI Listing

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