Predicting XXXX surgery time based on preoperative risk assessment.

@entity1 @entity231
PURPOSE: Operating room (OR) time is an expensive resource that should be optimized to reduce costs. Individual preoperative risk parameters (PORS) assessment may aid in predicting @entity231 surgery time. METHODS: Dedicated software was developed and known risk factors for @entity231 surgery were integrated into it. Preoperative risk parameters were assigned to each @entity1 in the preoperative meeting and the risk score was calculated. A total of 153 @entity1 were divided according to a standard classification into low-risk group (PORS  <=2) and high-risk group (PORS >5). Duration of surgery for each group was compared by Student t test and linear regression analysis was used to calculate the relation between change in OR time and change in risk score. RESULTS: @entity1 in the high PORS group had longer surgery times when compared with @entity1 in the low PORS group (37.6 vs 19.6, p<0.001). Risk scores positively correlated with surgery time (r = 0.30, p<0.001). Prediction equations for the OR time demonstrated for 2 surgeons that every increase in 1 risk point added 2.2 or 3.3 minutes to the OR time. Outliers (more than 1 standard deviation [SD] from each surgeon's surgery mean time) had more than twice the risk score of cases within 1 SD from the mean. CONCLUSIONS: The PORS system may be a useful tool for predicting OR time based on individual @entity1 risk and may improve OR scheduling.
