The Impact of Overestimations of Surgical Control Times Across Multiple Specialties on Medical Systems

J Med Syst. 2016 Apr;40(4):95. doi: 10.1007/s10916-016-0457-x. Epub 2016 Feb 10.


Optimization of operating room (OR) resources and costs require accurate estimations of procedure times. In some institutions, surgeons are asked to predict their surgical control time (SCT), which typically constitutes the majority of the total procedure time. Here, we examine differences in predicted versus actual SCT and variations by specialty. Data included all scheduled surgical procedures at one academic institution from October 2008 - September 2014. Exclusion criteria consisted of missing values for SCT as well as estimated SCTs that fell outside of 5 standard deviations of any given procedure's mean. Differences in estimation were calculated by subtracting estimated SCT from actual SCT and compared against a null hypothesis of 0 with a two-tailed t-test. Differences between specialties were examined using analysis of variance and Games-Howell tests. Between 2008 and 2014, 119,410 scheduled procedures were performed. After exclusion, 116,599 cases were analyzed. On average, SCT was overestimated by 12.9 min (p < 0.0001). Overestimations persisted when divided by specialty (p < 0.0001). With thoracic surgery as a control, all other specialties except for cardiac surgery had overestimations of SCT. The greatest time differences were seen in dental (37.6 min, p < 0.0001), cardiology (33.0 min, p < 0.0001), and neurosurgery (29.7 min, p < 0.0001). Overall, SCTs are overestimated at this institution across many specialties. Depending on the methodology by which a hospital chooses to allocate OR time, SCT estimations could potentially be reduced in certain specialties to allow for better allocation of OR resources.

Keywords: OR benchmarks; OR efficiency; OR management; Surgical control time.

MeSH terms

  • Appointments and Schedules
  • Benchmarking
  • Efficiency, Organizational*
  • Humans
  • Medicine / statistics & numerical data*
  • Operating Rooms / statistics & numerical data*
  • Operative Time*
  • Time Factors