Ontario Health (Cancer Care Ontario) (Wang, Vahid, Eberg, Milroy, Milkovich, Wright, Hunter, Zanchetta, Irish); Division of General Surgery (Wright), Sunnybrook Health Sciences Centre; Trillium Gift of Life Network (Kalladeen); Schulich Heart Centre (Wijeysundera), Sunnybrook Health Sciences Centre; Division of Cardiology (Wijeysundera), Department of Medicine and Department of Otolaryngology-Head and Neck Surgery/Surgical Oncology (Irish), Princess Margaret Cancer Centre/University Health Network, University of Toronto, Toronto, Ont.
CMAJ. 2020 Nov 2;192(44):E1347-E1356. doi: 10.1503/cmaj.201521. Epub 2020 Sep 1.
To mitigate the effects of coronavirus disease 2019 (COVID-19), jurisdictions worldwide ramped down nonemergent surgeries, creating a global surgical backlog. We sought to estimate the size of the nonemergent surgical backlog during COVID-19 in Ontario, Canada, and the time and resources required to clear the backlog.
We used 6 Ontario or Canadian population administrative sources to obtain data covering part or all of the period between Jan. 1, 2017, and June 13, 2020, on historical volumes and operating room throughput distributions by surgery type and region, and lengths of stay in ward and intensive care unit (ICU) beds. We used time series forecasting, queuing models and probabilistic sensitivity analysis to estimate the size of the backlog and clearance time for a +10% (+1 day per week at 50% capacity) surge scenario.
Between Mar. 15 and June 13, 2020, the estimated backlog in Ontario was 148 364 surgeries (95% prediction interval 124 508-174 589), an average weekly increase of 11 413 surgeries. Estimated backlog clearance time is 84 weeks (95% confidence interval [CI] 46-145), with an estimated weekly throughput of 717 patients (95% CI 326-1367) requiring 719 operating room hours (95% CI 431-1038), 265 ward beds (95% CI 87-678) and 9 ICU beds (95% CI 4-20) per week.
The magnitude of the surgical backlog from COVID-19 raises serious implications for the recovery phase in Ontario. Our framework for modelling surgical backlog recovery can be adapted to other jurisdictions, using local data to assist with planning.
为减轻 2019 年冠状病毒病（COVID-19）的影响，全球各地的司法管辖区纷纷减少非紧急手术，从而造成全球手术积压。我们试图估计加拿大安大略省 COVID-19 期间非紧急手术积压的规模，以及清除积压所需的时间和资源。
我们使用了 6 个安大略省或加拿大人口行政数据源，获取了 2017 年 1 月 1 日至 2020 年 6 月 13 日期间部分或全部的手术类型和地区手术量和手术室吞吐量分布、病房和重症监护病房（ICU）床位停留时间的数据。我们使用时间序列预测、排队模型和概率敏感性分析来估计积压量和每周增加 10%（每周增加 50%的手术容量增加 1 天）的积压清除时间。
2020 年 3 月 15 日至 6 月 13 日期间，安大略省估计的积压手术量为 148364 例（95%预测区间为 124508-174589 例），每周平均增加 11413 例手术。积压清除时间估计为 84 周（95%置信区间[CI]为 46-145），每周预计需要处理 717 名患者（95%CI 为 326-1367），需要 719 个手术室小时（95%CI 为 431-1038）、265 张病房床位（95%CI 为 87-678）和每周 9 张 ICU 床位（95%CI 为 4-20）。
COVID-19 造成的手术积压规模对安大略省的恢复阶段产生了严重影响。我们用于模拟手术积压恢复的框架可以使用本地数据进行修改，以适用于其他司法管辖区，以协助规划。
