“计划外缺勤”是指员工不上班且未得到授权主管事先批准的情况。在进行员工调度时,需要预测每日计划外缺勤,以保持无法运行所有麻醉地点和计划中的手术室的可接受风险。要安排的额外人员数量需要至少是平均缺勤人数的两倍。在早期的历史队列研究中,我们发现,我们部门的建模风险不可用,在麻醉从业人员的类型之间存在意外差异(例如,麻醉师和护士麻醉师)和工作日(即周一,星期五,与假期相邻的工作日与其他工作日)。在目前的研究中,再加上两年的数据,我们研究了冠状病毒COVID-19大流行对计划外缺勤频率的影响.方法在美国一家大型教学医院进行了50个为期四周的研究,从2018年8月30日至2022年6月29日。120,687个人分配日的样本量(即,分配给某一天工作的人)包括322名麻醉医生(86名麻醉医生,88名注册护士麻醉师,99名住院医师和医生同事,和49名学生护士麻醉师)。COVID-19的社区患病率是使用无症状患者在医院手术和其他介入手术前检测的阳性百分比来估计的。结果无症状患者中COVID-19患病率每增加1%,计划外缺席的几率增加1.131(P<0.0001,99%置信区间1.086至1.178)。使用具有患病率类别的替代模型,当COVID-19患病率超过2.50%时,计划外缺勤更常见,P[公式:见正文]0.0002。例如,在大流行早期周一和周五工作的麻醉医师中,有1%的计划外缺勤率,而COVID-19在无症状患者中的患病率为1.3%.以1%的计划外缺勤率,67将是不能运行所有65个麻醉位置的维持<5.0%风险的最低计划。相比之下,在Omicron变异型激增期间,周一和周五工作的护士麻醉师的计划外缺勤率为3%,患病率为4.5%.以3%的计划外缺勤率,70将是最低计划,以保持无法运行65个房间的相同风险。结论COVID-19无症状检测的患病率增加与更多的计划外缺席有关,没有检测到的阈值。这种对传染病对劳动力影响的定量理解可能对其他领域和传染病具有广泛的普遍性。
Introduction An \"unscheduled absence\" refers to an occurrence when an employee does not appear for work and the absence was not approved in advance by an authorized supervisor. Daily unscheduled absences need to be forecasted when doing staff scheduling to maintain an acceptable risk of being unable to run all anesthetizing locations and operating rooms planned. The number of extra personnel to be scheduled needs to be at least twice as large as the mean number absent. In an earlier historical cohort study, we found that our department\'s modeled risks of being unavailable unexpectedly differed among types of anesthesia practitioners (e.g., anesthesiologists and nurse anesthetists) and among weekdays (i.e., Mondays, Fridays, and workdays adjacent to holidays versus other weekdays). In the current study, with two extra years of data, we examined the effect of the coronavirus COVID-19 pandemic on the frequency of unscheduled absences. Methods There were 50 four-week periods studied at a large teaching hospital in the United States, from August 30, 2018 to June 29, 2022. The sample size of 120,687 person-assignment days (i.e., a person assigned to work on a given day) included 322 anesthesia practitioners (86 anesthesiologists, 88 certified registered nurse anesthetists, 99 resident and fellow physicians, and 49 student nurse anesthetists). The community prevalence of COVID‑19 was estimated using the percentage positive among asymptomatic patients tested before surgery and other interventional procedures at the hospital. Results Each 1% increase in the prevalence of COVID-19 among asymptomatic patients was associated with a 1.131 increase in the odds of unscheduled absence (P < 0.0001, 99% confidence interval 1.086 to 1.178). Using an alternative model with prevalence categories, unscheduled absences were substantively more common when the COVID-19 prevalence exceeded 2.50%, P [Formula: see text] 0.0002. For example, there was a 1% unscheduled absence rate among anesthesiologists working Mondays and Fridays early in the pandemic when the prevalence of COVID-19 among asymptomatic patients was 1.3%. At a 1% unscheduled absence rate, 67 would be the minimum scheduled to maintain a <5.0% risk for being unable to run all 65 anesthetizing locations. In contrast, there was a 3% unscheduled absence rate among nurse anesthetists working Mondays and Fridays during the Omicron variant surge when the prevalence was 4.5%. At a 3% unscheduled absence rate, 70 would be the minimum scheduled to maintain the same risk of not being able to run 65 rooms. Conclusions Increases in the prevalence of COVID-19 asymptomatic tests were associated with more unscheduled absences, with no detected threshold. This quantitative understanding of the impact of communicable diseases on the workforce potentially has broad generalizability to other fields and infectious diseases.