Abstract
For efficient utilization of operating rooms (ORs), accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT) per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT) and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA) physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT). We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT). TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related benefits.
Highlights
Operating rooms (ORs) are some of the most valuable hospital assets there are, generating a large part of hospital revenue
For efficient utilization of operating rooms (ORs), accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT; abbreviations are described in Table 1) per case
We attempt to improve the accuracy of TPT predictions further by including patient and surgery characteristics relevant to TPT
Summary
Operating rooms (ORs) are some of the most valuable hospital assets there are, generating a large part of hospital revenue. Revenue per OR hour varies per procedure, but is estimated to be between $1,000 and $2,000 on average, before subtracting the variable costs of personnel and supplies related to hospitalization [1] This makes efficient utilization of ORs paramount. For efficient utilization of ORs, accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT; abbreviations are described in Table 1) per case. TPT consists of anesthesiacontrolled time (ACT, itself consisting of the induction and emergence phases) and surgeon-controlled time (SCT, being the duration of the actual operation, including patient positioning and draping). ACT is included because in Dutch academic hospitals, the induction and emergence phases always take place in the OR, making them relevant to OR utilization
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