BACKGROUND: Surgical cancellation rates typically are reported as the number of cancelled cases divided by the number of scheduled cases. However, the total number of cancelled minutes also has financial impact on surgeons' productivity. Cancellation rates can instead be calculated based on the number of minutes of cancelled cases. Hospitals typically benchmark cancellation rates, since not all cancellations are preventable (e.g., those due to new onset of patient symptoms requiring further workup and treatment before surgery can safely proceed). If the mean estimated duration of cancelled cases were the same as that of scheduled cases, rates would be equivalent whether calculated using the number of cancellations or the minutes of cancellations. It is unknown whether there is a difference between these 2 methods. METHODS: Data for elective, regular workday cases scheduled were obtained from 2 academic hospitals and binned into 8 sequential 13-week periods. Cancellation rates after 7:00 am or after 7:00 pm on the working day before surgery were calculated by service as (1) the numeric cancellation rate = number cancelled divided by the number scheduled and (2) the duration cancellation rate = minutes cancelled divided by the minutes scheduled. Mean differences (biases) and 95% prediction limits between the numeric and duration cancellation rates were determined. RESULTS: The hospitals' numeric cancellation rates after 7:00 am (11.6% and 10.7%) were similar to 12.2% from an academic hospital survey. Bias by individual service ranged from -1.16% ± 1.34% to 1.93% ± 3.01% at one hospital and -1.08% ± 2.76% to 3.05% ± 1.89% at the other. Mean differences between matching services at the hospitals were -0.7% ± 0.6% to 3.3% ± 0.3%. There was considerable variability among services for numeric cancellation rates and the prediction limits of the cancellation rate, calculated using the number of minutes cancelled. CONCLUSIONS: Calculating cancellation rates using case counts can inaccurately represent their impact on surgeon's productivity compared with using minutes of cancelled cases. Comparing numeric cancellation rates between hospitals or services without checking for bias may lead to inappropriate conclusions. We recommend that hospitals evaluate their data for potential bias to determine whether cancellation rates need to be calculated using scheduled minutes of cases rather than numbers of cancellations.
BACKGROUND: Surgical cancellation rates typically are reported as the number of cancelled cases divided by the number of scheduled cases. However, the total number of cancelled minutes also has financial impact on surgeons' productivity. Cancellation rates can instead be calculated based on the number of minutes of cancelled cases. Hospitals typically benchmark cancellation rates, since not all cancellations are preventable (e.g., those due to new onset of patient symptoms requiring further workup and treatment before surgery can safely proceed). If the mean estimated duration of cancelled cases were the same as that of scheduled cases, rates would be equivalent whether calculated using the number of cancellations or the minutes of cancellations. It is unknown whether there is a difference between these 2 methods. METHODS: Data for elective, regular workday cases scheduled were obtained from 2 academic hospitals and binned into 8 sequential 13-week periods. Cancellation rates after 7:00 am or after 7:00 pm on the working day before surgery were calculated by service as (1) the numeric cancellation rate = number cancelled divided by the number scheduled and (2) the duration cancellation rate = minutes cancelled divided by the minutes scheduled. Mean differences (biases) and 95% prediction limits between the numeric and duration cancellation rates were determined. RESULTS: The hospitals' numeric cancellation rates after 7:00 am (11.6% and 10.7%) were similar to 12.2% from an academic hospital survey. Bias by individual service ranged from -1.16% ± 1.34% to 1.93% ± 3.01% at one hospital and -1.08% ± 2.76% to 3.05% ± 1.89% at the other. Mean differences between matching services at the hospitals were -0.7% ± 0.6% to 3.3% ± 0.3%. There was considerable variability among services for numeric cancellation rates and the prediction limits of the cancellation rate, calculated using the number of minutes cancelled. CONCLUSIONS: Calculating cancellation rates using case counts can inaccurately represent their impact on surgeon's productivity compared with using minutes of cancelled cases. Comparing numeric cancellation rates between hospitals or services without checking for bias may lead to inappropriate conclusions. We recommend that hospitals evaluate their data for potential bias to determine whether cancellation rates need to be calculated using scheduled minutes of cases rather than numbers of cancellations.