Dexter Franklin, Epstein Richard H, Sondekoppam Rakesh V, Marian Anil A
Department of Anesthesia, University of Iowa, 200 Hawkins Drive, Iowa City, IA, 52242, United States of America.
Department of Anesthesiology, Perioperative Medicine & Pain Management, University of Miami, Miami, FL, USA.
J Med Syst. 2025 Apr 17;49(1):48. doi: 10.1007/s10916-025-02179-y.
When multiple patients are scheduled to receive regional blocks as part of their anesthetic, planning insufficient preoperative time can cause first-case operating room delays. Prediction of the time to perform multiple regional blocks depends on the probability distributions (e.g., 90th percentiles) of the procedure completion times. We tested hypotheses that, if supported, can be applied for planning how early regional blocks should start to mitigate late first-case of the day starts. The retrospective cohort study used data from two academic hospital surgical suites for all regional anesthetic procedures performed before the adult patients entered the operating room for a first-case of the day. Days with more total minutes of regional procedures had greater total lateness (negative if early) and tardiness (zero if early) of first-case starts for both suites (all four Bonferroni adjusted P < 0.0001). Increases in the numbers of procedures per day were not associated with significant differences in the 0.5 quantile (median) among days of the time per procedure for both the inpatient surgical suite (unadjusted P = 0.46) and the ambulatory surgery center (P = 0.14). The result supported our hypothesis that average times add arithmetically among procedures. Increases in the numbers of procedures per day were associated with significant decreases in the 0.9 quantile among days of the time per procedure for both the inpatient surgical suite (-0.83 min per procedure, Bonferroni adjusted P < 0.0001) and the ambulatory surgery center (-0.90 min per procedure, adjusted P = 0.0002). Because both slopes were reliably negative, the result supported our second hypothesis that the longest time to plan to complete a series of procedures (represented by the 0.9 quantile) is considerably less than as calculated by taking the sum of the individual procedures' 0.9 quantiles. Quantile regression or an Excel 365 formula based on the log-normal distribution for block times can consequently be used to predict the time when anesthesiologists should start procedures and have a low risk of causing first-case start delays. For example, with 7 blocks, the sum of individual 0.9 quantiles would suggest that the anesthesiologist needs to start ≈35 min earlier than necessary based on the 0.9 quantile. Sufficient time can be planned to perform multiple procedures before the first-case of the day starts using quantile regression or an Excel formula. The estimated times are briefer than the sum of the 0.9 quantiles, but longer than the sum of the 0.5 quantiles.
当安排多名患者接受区域阻滞作为麻醉的一部分时，术前时间规划不足可能会导致当日第一台手术延迟进入手术室。预测进行多次区域阻滞所需的时间取决于手术完成时间的概率分布（例如，第90百分位数）。我们对一些假设进行了检验，若这些假设得到支持，便可应用于规划区域阻滞应多早开始，以减少当日第一台手术的延迟开始情况。这项回顾性队列研究使用了来自两家学术医院手术科室的数据，这些数据涵盖了成年患者在当日第一台手术进入手术室之前所进行的所有区域麻醉手术。两个科室中，区域手术总时长较长的日子，当日第一台手术开始的总延迟时间（提前则为负数）和迟到时间（提前则为零）都更大（所有四个经Bonferroni校正的P值均<0.0001）。对于住院手术科室（未校正P值=0.46）和门诊手术中心（P值=0.14），每日手术数量的增加与每次手术时间的0.5分位数（中位数）在不同日子之间的显著差异无关。该结果支持了我们的假设，即手术时间的平均值是算术累加的。对于住院手术科室（每次手术-0.83分钟，经Bonferroni校正的P值<0.0001）和门诊手术中心（每次手术-0.90分钟，校正后的P值=0.0002），每日手术数量的增加与每次手术时间的0.9分位数在不同日子之间的显著减少相关。由于这两个斜率均可靠地为负数，该结果支持了我们的第二个假设，即计划完成一系列手术的最长时间（由0.9分位数表示）远小于将各个手术的0.9分位数相加所计算出的时间。因此，分位数回归或基于阻滞时间对数正态分布的Excel 365公式可用于预测麻醉医生应开始手术的时间，且导致第一台手术开始延迟的风险较低。例如，对于7次阻滞，各个0.9分位数的总和表明，根据0.9分位数，麻醉医生需要比必要时间提前约35分钟开始。使用分位数回归或Excel公式，可以在当日第一台手术开始前规划出足够的时间来进行多次手术。估计时间比0.9分位数的总和短，但比0.5分位数的总和长。
