title: Discharge decision-making after complex surgery: Surgeon behaviors compared to predictive modeling to reduce surgical readmissions.
abstract: BACKGROUND
  Little is known about how information available at discharge affects decision-making and its effect on readmission. We sought to define the association between information used for discharge and patients' subsequent risk of readmission.
  
  
  METHODS
  2009-2014 patients from a tertiary academic medical center's surgical services were analyzed using a time-to-event model to identify criteria that statistically explained the timing of discharges. The data were subsequently used to develop a time-varying prediction model of unplanned hospital readmissions. These models were validated and statistically compared.
  
  
  RESULTS
  The predictive discharge and readmission regression models were generated from a database of 20,970 patients totaling 115,976 patient-days with 1,565 readmissions (7.5%). 22 daily clinical measures were significant in both regression models. Both models demonstrated good discrimination (C statistic = 0.8 for all models). Comparison of discharge behaviors versus the predictive readmission model suggested important discordance with certain clinical measures (e.g., demographics, laboratory values) not being accounted for to optimize discharges.
  
  
  CONCLUSIONS
  Decision-support tools for discharge may utilize variables that are not routinely considered by healthcare providers. How providers will then respond to these atypical findings may affect implementation.
authors.affiliation: Department of Surgery, The Johns Hopkins Hospital, 600 N Wolfe Street, Tower 110, Baltimore, MD 21287, USA; Department of Surgery, Emory University School of Medicine, 201 Dowman Drive, Atlanta, GA 30322, USA. Electronic address: ileeds@jhmi.edu.
authors.forename: Ira L
authors.initials: IL
authors.lastname: Leeds
authors.affiliation: Department of Economics and Experimental Economics Center, Georgia State University, 14 Marietta Street NW, Atlanta, GA 30303, USA.
authors.forename: Vjollca
authors.initials: V
authors.lastname: Sadiraj
authors.affiliation: Department of Economics and Experimental Economics Center, Georgia State University, 14 Marietta Street NW, Atlanta, GA 30303, USA.
authors.forename: James C
authors.initials: JC
authors.lastname: Cox
authors.affiliation: Department of Economics and Experimental Economics Center, Georgia State University, 14 Marietta Street NW, Atlanta, GA 30303, USA.
authors.forename: Xiaoxue Sherry
authors.initials: XS
authors.lastname: Gao
authors.affiliation: Department of Surgery, The Johns Hopkins Hospital, 600 N Wolfe Street, Tower 110, Baltimore, MD 21287, USA.
authors.forename: Timothy M
authors.initials: TM
authors.lastname: Pawlik
authors.affiliation: School of Social Sciences, Humanities and Arts, University of California - Merced, 5200 N Lake Road, Merced, CA 95343, USA.
authors.forename: Kurt E
authors.initials: KE
authors.lastname: Schnier
authors.affiliation: Department of Surgery, Emory University School of Medicine, 201 Dowman Drive, Atlanta, GA 30322, USA.
authors.forename: John F
authors.initials: JF
authors.lastname: Sweeney
mesh_terms: D000046:Academic Medical Centers; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001291:Attitude of Health Personnel; D015331:Cohort Studies; D016208:Databases, Factual; D003658:Decision Making, Computer-Assisted; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D015994:Incidence; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010359:Patient Readmission / Q000706:statistics & numerical data*; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D018570:Risk Assessment; D066231:Surgeons / Q000523:psychology; D013514:Surgical Procedures, Operative / Q000009:adverse effects* / Q000379:methods; D062606:Tertiary Care Centers; D014481:United States; D055815:Young Adult
keywords: Computer-assisted decision-making; Decision support; Hospital readmission; Logit model