title: Predictors of 30-day readmission after mastectomy: A multi-institutional analysis of 21,271 patients.
abstract: BACKGROUND
  Recent healthcare legislation has made unplanned hospital readmission an important metric of health care quality, and current efforts center on reducing this complication in order to avoid fiduciary penalties.
  
  
  OBJECTIVE
  There is currently a paucity of data delineating risk factors for readmission following mastectomy. To this end, we sought to develop a predictive model of unplanned readmissions following mastectomy.
  
  
  METHODS
  The 2011 and 2012 National Surgical Quality Improvement Program (NSQIP) datasets were retrospectively queried to identify patients who underwent mastectomy. Multivariate logistic regression modeling was used to identify risk factors for readmission.
  
  
  RESULTS
  Of 21,271 patients meeting inclusion criteria, 1,190 (5.59%) were readmitted. The most commonly cited reasons for readmission included surgical site complications (32.85%), infection not localized to the surgical site (2.72%), and venous thromboembolism (4.39%). Independent predictors of readmission included BMI, active smoking status, and skin-sparing mastectomy. Significantly, concurrent breast reconstruction and bilateral mastectomy were not independent predictors of readmission.
  
  
  CONCLUSIONS
  This is the first study of readmission rates after mastectomy. Awareness of specific risk factors for readmission, particularly those that are modifiable, may serve to identify and manage high risk patients, aid in the development of pre- and postoperative clinical care guidelines, and ultimately improve patient care.
authors.affiliation: Division of Plastic and Reconstructive Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
authors.forename: Ian
authors.initials: I
authors.lastname: Chow
authors.affiliation: Division of Plastic and Reconstructive Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
authors.forename: Philip J
authors.initials: PJ
authors.lastname: Hanwright
authors.affiliation: Lynn Sage Comprehensive Breast Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
authors.forename: Nora M
authors.initials: NM
authors.lastname: Hansen
authors.affiliation: Division of Plastic and Reconstructive Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
authors.forename: Solmaz N
authors.initials: SN
authors.lastname: Leilabadi
authors.affiliation: Division of Plastic and Reconstructive Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
authors.forename: John Y S
authors.initials: JY
authors.lastname: Kim
mesh_terms: D000328:Adult; D000368:Aged; D019540:Area Under Curve; D015992:Body Mass Index; D005260:Female; D005544:Forecasting / Q000379:methods; D006801:Humans; D016015:Logistic Models; D008408:Mastectomy / Q000009:adverse effects* / Q000706:statistics & numerical data*; D008875:Middle Aged; D015999:Multivariate Analysis; D059351:Organ Sparing Treatments / Q000009:adverse effects / Q000706:statistics & numerical data; D010359:Patient Readmission / Q000706:statistics & numerical data*; D012372:ROC Curve; D012189:Retrospective Studies; D012307:Risk Factors; D012907:Smoking; D013530:Surgical Wound Infection / Q000209:etiology*; D013997:Time Factors; D054556:Venous Thromboembolism / Q000209:etiology*
keywords: 30-day; mastectomy; outcomes; readmission; risk factors