title: Use of simulation to assess a statistically driven surgical scheduling system.
abstract: BACKGROUND
  To maximize operating room (OR) utilization, better estimates of case duration lengths are needed. We used computerized simulation to determine whether scheduling OR cases using a statistically driven system that incorporates patient and surgery-specific factors in the process of case duration prediction improves OR throughput and utilization.
  
  
  METHODS
  We modeled surgical and anesthetic length of vascular surgical procedures as a function of patient and operative characteristics using a multivariate linear regression approach (Predictive Modeling System [PMS]). Mean historical operative time per surgeon (HMS) and mean anesthetic time were also calculated for each procedure type. A computerized simulation of scheduling in a single OR performing vascular operations was then created using either the PMS or the HMS.
  
  
  RESULTS
  Compared to HMS, scheduling the operating room using the PMS increased throughput by a minimum of 15% (99.8% cumulative probability, P < 0.001). The PMS was slightly more likely to lead to overtime (mean 13% versus 11% of operative days during a calendar year, P < 0.001). However, the overtime lasted longer in the HMS group (mean 140 versus 95 min per day of overtime, P < 0.001). PMS was associated with lower OR underutilization rate (mean 23% versus 34% of operative days, P < 0.001) and less lengthy OR underutilization (mean 120 versus 193 min per day of underutilization, P < 0.001).
  
  
  CONCLUSIONS
  This computerized simulation demonstrates that using the PMS for scheduling in a single operating room increases throughput and other measures of surgical efficiency.
authors.affiliation: Michael E. DeBakey VA Medical Center, Houston, Texas; Division of Vascular Surgery, Baylor College of Medicine, Houston, Texas; Center for Innovation, Quality, Effectiveness and Safety, Houston, Texas. Electronic address: pkougias@bcm.edu.
authors.forename: Panos
authors.initials: P
authors.lastname: Kougias
authors.affiliation: Department of Anesthesiology, Vanderbilt University, Nashville, Tennessee.
authors.forename: Vikram
authors.initials: V
authors.lastname: Tiwari
authors.affiliation: Michael E. DeBakey VA Medical Center, Houston, Texas; Center for Innovation, Quality, Effectiveness and Safety, Houston, Texas; Department of Surgery, Baylor College of Medicine, Houston, Texas.
authors.forename: David H
authors.initials: DH
authors.lastname: Berger
mesh_terms: D001071:Appointments and Schedules; D003198:Computer Simulation; D006801:Humans; D015233:Models, Statistical; D009870:Operating Room Information Systems; D009873:Operating Rooms / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D014656:Vascular Surgical Procedures
keywords: Effectiveness; Simulation; Statistical modeling