title: Maximizing operating room and recovery room capacity in an era of constrained resources.
abstract: OBJECTIVE
  Three parallel processing operating rooms (ORs) (concurrent induction and turnover) with a dedicated 3-bed mini-recovery room (mini-postanesthesia care unit [PACU]) will optimize patient throughput and main PACU workload when compared with 4 traditional ORs or 4 parallel processing ORs.
  
  
  METHODS
  Statistical and mathematical models projected the impact of parallel processing on case throughput and PACU use.
  
  
  METHODS
  Academic medical center with 48 traditional ORs using serial induction and turnover and 1 experimental OR, the operating room of the future, with parallel processing.
  
  
  METHODS
  All surgical cases from October 2002 through March 2004 (N = 49 887).
  
  
  METHODS
  A statistical model projected the duration of induction, surgery, turnover, and PACU stay for cases performed in a traditional OR (n = 48 667) based on the operating room of the future (n = 1220) experience. A fluid queuing model compared each combination using specific probability density functions.
  
  
  METHODS
  Each OR configuration was evaluated for case throughput and minutes of work sent to the PACU.
  
  
  RESULTS
  Although all cases save OR time with parallel processing, only select surgeon-case combinations translate time saved into additional cases per day (26%). Without additional PACU slots, output from 4 parallel processing ORs further stresses the PACU. Three parallel processing ORs and a mini-PACU balances incremental volume by offsetting PACU utilization in 84% of cases.
  
  
  CONCLUSIONS
  In a PACU-constrained environment, 3 parallel processing ORs with a mini-PACU configuration offers increased throughput and decreased PACU workload.
authors.affiliation: Center for Clinical Effectiveness in Surgery and Department of Surgery, Massachusetts General Hospital, Boston 02114, USA.
authors.forename: Suzanne M
authors.initials: SM
authors.lastname: Sokal
authors.forename: David L
authors.initials: DL
authors.lastname: Craft
authors.forename: Yuchiao
authors.initials: Y
authors.lastname: Chang
authors.forename: Warren S
authors.initials: WS
authors.lastname: Sandberg
authors.forename: David L
authors.initials: DL
authors.lastname: Berger
mesh_terms: D000046:Academic Medical Centers; D006801:Humans; D015233:Models, Statistical; D009873:Operating Rooms / Q000706:statistics & numerical data*; D011997:Recovery Room / Q000706:statistics & numerical data*; D017748:Time Management; D016526:Workload