title: Predicting who will fail early discharge after laparoscopic colorectal surgery with an established enhanced recovery pathway.
abstract: BACKGROUND
  Despite using laparoscopy and enhanced recovery pathways (ERP), some patients are not ready for early discharge. The goal of this study was to identify predictors for patients who might fail early discharge, so that any defined factors might be addressed and optimized.
  
  
  METHODS
  A prospectively maintained database was reviewed for major elective laparoscopic colorectal surgical procedures. Cases were divided into day of discharge groups: ≤ 3 days and >4 days. All followed a standardized ERP. Demographic and clinical data were compared using Student's paired t tests or Fisher's exact test, with p value < 0.05 statistically significant. Regression analysis was performed to identify significant variables.
  
  
  RESULTS
  There were 275 ≤ 3 days patients and 273 >4 days patients. There were significant differences between groups in body mass index (p = 0.0123), comorbidities (p = 0.0062), ASA class (p = 0.0014), operation time (p < 0.001), postoperative complications (p < 0.001), and 30-day reoperation rate (p = 0.0004). There were no significant differences for intraoperative complications (p = 0.724), readmissions (p = 0.187), or mortality rate (p = 1.00). Significantly more patients were discharged directly home in the ≤ 3-days cohort. Using logistic regression, every hour of operating time increased the risk of length of stay >4 days by 2.35 %.
  
  
  CONCLUSIONS
  Elective colorectal surgery patients with longer operation times and more comorbidities are more likely to fail early discharge. These patients should have different expectations of the ERP, as an expected 1- to 3-day stay may not be achievable. By identifying patients at risk for failing early discharge, resources and postoperative support can be better allocated and patients better informed about likely recovery.
authors: Division of Colorectal Surgery, Department of Surgery, University Hospitals-Case Medical Center, 11100 Euclid Ave, Cleveland, OH, 44106-5047, USA, debby_keller@hotmail.com.
authors: Deborah S
authors: DS
authors: Keller
authors: Blake
authors: B
authors: Bankwitz
authors: Donya
authors: D
authors: Woconish
authors: Bradley J
authors: BJ
authors: Champagne
authors: Harry L
authors: HL
authors: Reynolds
authors: Sharon L
authors: SL
authors: Stein
authors: Conor P
authors: CP
authors: Delaney
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D015992:Body Mass Index; D003082:Colectomy / Q000706:statistics & numerical data; D003107:Colorectal Surgery / Q000706:statistics & numerical data*; D015897:Comorbidity; D019091:Critical Pathways / Q000706:statistics & numerical data*; D016208:Databases, Factual; D017558:Elective Surgical Procedures / Q000706:statistics & numerical data; D005260:Female; D006801:Humans; D010535:Laparoscopy / Q000706:statistics & numerical data*; D007902:Length of Stay / Q000706:statistics & numerical data; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D061646:Operative Time; D010351:Patient Discharge / Q000706:statistics & numerical data*; D011183:Postoperative Complications / Q000453:epidemiology; D011237:Predictive Value of Tests; D012086:Reoperation; D012189:Retrospective Studies; D016896:Treatment Outcome
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