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Validity and usefulness of a method to monitor surgical services' average bias in scheduled case durations
Journal article   Open access   Peer reviewed

Validity and usefulness of a method to monitor surgical services' average bias in scheduled case durations

Franklin Dexter, Alex Macario, Richard H Epstein and Johannes Ledolter
Canadian journal of anaesthesia = Journal canadien d'anesthesie, Vol.52(9), pp.935-939
11/2005
DOI: 10.1007/BF03022054
PMID: 16251558
url
https://doi.org/10.1007/BF03022054View
Published (Version of record) Open Access

Abstract

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. 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. 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. 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.
 Operating Rooms - organization & administration Workload - statistics & numerical data Operating Rooms - manpower Operating Rooms - statistics & numerical data Bias Models, Statistical Academic Medical Centers

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