Validity and usefulness of a method to monitor surgical services' average bias in scheduled case durations.
OBJECTIVE
Unbiased prediction of case durations is an integral part of matching operating room (OR) staffing to workload. Monitoring systematic bias in surgeons' scheduled case durations can identify those services with estimates sufficiently inaccurate that statistical analysis of historical data may be useful in preference to the surgeons' estimates. We describe a method to monitor surgical services' average bias in scheduled case durations.


METHODS
Actual case duration, predicted (scheduled) case duration, and service were obtained for all 58,291 cases during 39 four-week periods at an academic hospital. For each four-week period, a ratio was computed for each service. The numerator for each service equalled the sum of the differences in minutes between actual case duration and scheduled case duration. The denominator equalled the sum in hours of the actual durations of all of the service's cases. The ratio was multiplied by eight hours to yield the number of minutes of underestimated case duration per eight hours of OR time during the four-week period.


RESULTS
The ratios followed a normal distribution for each service. Using the Student's t distribution, the 95% lower confidence bounds for the average underestimate of case duration ranged from three to 65 min per eight hours of used OR time.


CONCLUSIONS
To reduce over-utilized OR time, we recommend monitoring each service's 95% lower confidence bound of the bias in scheduled case durations. For services consistently underestimating their case durations, schedule their cases using statistical estimates of case durations based on their historical data, and disregard their own estimates.
Dexter
Franklin
F
Division of Management Consulting, Department of Anesthesia, 6-JCP, University of Iowa, Iowa City, Iowa 52242, USA. Franklin-Dexter@UIowa.edu
Macario
Alex
A
Epstein
Richard H
RH
Ledolter
Johannes
J
D000046:Academic Medical Centers; D015982:Bias; D015233:Models, Statistical; D009873:Operating Rooms / Q000458:organization & administration* / Q000706:statistics & numerical data*; D000078329:Workforce; D016526:Workload / Q000706:statistics & numerical data*