Division of Biostatistics, Graduate School of Medicine, Tohoku University, Miyagi, Japan.
Clinical Research Data Center, Tohoku University Hospital, Miyagi, Japan.
Clin Trials. 2021 Apr;18(2):158-167. doi: 10.1177/1740774520971254. Epub 2020 Dec 1.
BACKGROUND/AIMS: Traditional on-site monitoring of clinical trials via frequent site visits and 100% source data verification is cost-consuming, and it still cannot guarantee data quality effectively. Depending on the types and designs of clinical trials, an alternative would be combining several monitoring methods, such as risk-based monitoring and remote monitoring. However, there is insufficient evidence of its effectiveness. This research compared the effectiveness of risk-based monitoring with a remote monitoring system with that of traditional on-site monitoring.
With a cloud-based remote monitoring system called beagle View, we created a remote risk-based monitoring methodology that focused only on critical data and processes. We selected a randomized controlled trial conducted at Tohoku University Hospital and randomly sampled 11 subjects whose case report forms had already been reviewed by data managers. Critical data and processes were verified retrospectively by remote risk-based monitoring; later, all data and processes were confirmed by on-site monitoring. We compared the ability of remote risk-based monitoring to detect critical data and process errors with that of on-site monitoring with 100% source data verification, including an examination of clinical trial staff workload and potential cost savings.
Of the total data points (n = 5617), 19.7% (n = 1105, 95% confidence interval = 18.7-20.7) were identified as critical. The error rates of critical data detected by on-site monitoring, remote risk-based monitoring, and data review by data managers were 7.6% (n = 84, 95% CI = 6.2-9.3), 7.6% (n = 84, 95% confidence interval = 6.2-9.3), and 3.9% (n = 43, 95% confidence interval = 2.9-5.2), respectively. The total number of critical process errors detected by on-site monitoring was 14. Of these 14, 92.9% (n = 13, 95% confidence interval = 68.5-98.7) and 42.9% (n = 6, 95% confidence interval = 21.4-67.4) of critical process errors were detected by remote risk-based monitoring and data review by data managers, respectively. The mean time clinical trial staff spent dealing with remote risk-based monitoring was 9.9 ± 5.3 (mean ± SD) min per visit per subject. Our calculations show that remote risk-based monitoring saved between 9 and 41 on-site monitoring visits, corresponding to a cost of between US$13,500 and US$61,500 per trial site.
Remote risk-based monitoring was able to detect critical data and process errors as well as on-site monitoring with 100% source data verification, saving travel time and monitoring costs. Remote risk-based monitoring offers an effective alternative to traditional on-site monitoring of clinical trials.
背景/目的:传统的临床试验现场监测通过频繁的现场访问和 100%的源数据验证,既耗费成本,又不能有效地保证数据质量。根据临床试验的类型和设计,可以选择结合几种监测方法,如基于风险的监测和远程监测。然而,其有效性的证据不足。本研究比较了基于风险的监测和远程监测系统与传统现场监测的效果。
我们使用名为 beagle View 的基于云的远程监测系统,创建了一种仅关注关键数据和流程的远程基于风险的监测方法。我们选择了在东北大学医院进行的一项随机对照试验,并随机抽取了 11 名已由数据管理员审查过病例报告表的受试者。通过远程基于风险的监测对关键数据和流程进行回顾性验证;之后,通过现场监测对所有数据和流程进行确认。我们比较了远程基于风险的监测与 100%源数据验证的现场监测检测关键数据和流程错误的能力,包括检查临床试验工作人员的工作量和潜在的成本节约。
在总共 5617 个数据点中,19.7%(n=1105,95%置信区间为 18.7-20.7)被确定为关键数据。现场监测、远程基于风险的监测和数据管理员数据审查检测到的关键数据错误率分别为 7.6%(n=84,95%置信区间为 6.2-9.3)、7.6%(n=84,95%置信区间为 6.2-9.3)和 3.9%(n=43,95%置信区间为 2.9-5.2)。现场监测共发现 14 个关键流程错误。其中,远程基于风险的监测和数据管理员数据审查分别检测到 92.9%(n=13,95%置信区间为 68.5-98.7)和 42.9%(n=6,95%置信区间为 21.4-67.4)的关键流程错误。临床试验工作人员处理远程基于风险监测的平均时间为每位受试者每次访问 9.9±5.3 分钟(平均值±标准差)。我们的计算表明,远程基于风险的监测可以节省 9 至 41 次现场监测访问,每个试验地点的成本节约为 13500 美元至 61500 美元。
远程基于风险的监测能够检测到关键数据和流程错误,与 100%源数据验证的现场监测效果相当,同时节省了旅行时间和监测成本。远程基于风险的监测为临床试验的传统现场监测提供了一种有效的替代方法。