title: Forecasting surgical groups' total hours of elective cases for allocation of block time: application of time series analysis to operating room management.
abstract: BACKGROUND
  Allocation of the correct amount of operating room (OR) "block time" can provide surgeons with access to sufficient OR time to complete their elective cases while optimally matching staffing with the elective case workload (to maximize labor productivity). To evaluate how to predict accurately total hours of elective cases performed by a surgical group using data from surgical services information systems, the authors addressed the following questions: (1) How many previous 4-week periods of data should be used to minimize error in forecasting a surgical group's total hours of elective cases? (2) Using the number of 4-week periods from question #1, can we detect trends or correlations between successive periods that could be used to improve forecasting accuracy? (3) How can results from questions #1 and #2 be used to calculate an upper prediction bound (upper limit) for the total hours of elective cases that will be completed in a future period? Prediction bounds can be used to budget staffing accurately.
  
  
  METHODS
  Time series analysis was performed on total hours of elective cases over 39 consecutive 4-week periods from 17 surgical groups.
  
  
  RESULTS
  The average of 12 consecutive periods' total hours of elective cases had an appropriate error profile. The observations within each series of 12 consecutive 4-week periods followed a normal distribution, with each observation of total hours of elective cases not correlated with the subsequent observation.
  
  
  CONCLUSIONS
  The average of the most recent 12 4-week periods can be used to predict surgical groups' future use of block time.
authors.affiliation: Department of Anesthesia, University of Iowa, Iowa City 52242, USA. franklin-dexter@uiowa.edu
authors.forename: F
authors.initials: F
authors.lastname: Dexter
authors.forename: A
authors.initials: A
authors.lastname: Macario
authors.forename: F
authors.initials: F
authors.lastname: Qian
authors.forename: R D
authors.initials: RD
authors.lastname: Traub
mesh_terms: D000465:Algorithms; D000758:Anesthesia; D001071:Appointments and Schedules; D003365:Costs and Cost Analysis; D017558:Elective Surgical Procedures; D006801:Humans; D009870:Operating Room Information Systems; D009873:Operating Rooms / Q000191:economics / Q000458:organization & administration*; D013997:Time Factors; D000078329:Workforce