Park Yu Rang, Koo HaYeong, Yoon Young-Kwang, Park Sumi, Lim Young-Suk, Baek Seunghee, Kim Hae Reong, Kim Tae Won
Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Republic of Korea.
Clinical Research Center, Asan Institute of Life Sciences, Asan Medical Center, Seoul, Republic of Korea.
JMIR Med Inform. 2020 Feb 23;8(2):e14379. doi: 10.2196/14379.
Early detection or notification of adverse event (AE) occurrences during clinical trials is essential to ensure patient safety. Clinical trials take advantage of innovative strategies, clinical designs, and state-of-the-art technologies to evaluate efficacy and safety, however, early awareness of AE occurrences by investigators still needs to be systematically improved.
This study aimed to build a system to promptly inform investigators when clinical trial participants make unscheduled visits to the emergency room or other departments within the hospital.
We developed the Adverse Event Awareness System (AEAS), which promptly informs investigators and study coordinators of AE occurrences by automatically sending text messages when study participants make unscheduled visits to the emergency department or other clinics at our center. We established the AEAS in July 2015 in the clinical trial management system. We compared the AE reporting timeline data of 305 AE occurrences from 74 clinical trials between the preinitiative period (December 2014-June 2015) and the postinitiative period (July 2015-June 2016) in terms of three AE awareness performance indicators: onset to awareness, awareness to reporting, and onset to reporting.
A total of 305 initial AE reports from 74 clinical trials were included. All three AE awareness performance indicators were significantly lower in the postinitiative period. Specifically, the onset-to-reporting times were significantly shorter in the postinitiative period (median 1 day [IQR 0-1], mean rank 140.04 [SD 75.35]) than in the preinitiative period (median 1 day [IQR 0-4], mean rank 173.82 [SD 91.07], P≤.001). In the phase subgroup analysis, the awareness-to-reporting and onset-to-reporting indicators of phase 1 studies were significantly lower in the postinitiative than in the preinitiative period (preinitiative: median 1 day, mean rank of awareness to reporting 47.94, vs postinitiative: median 0 days, mean rank of awareness to reporting 35.75, P=.01; and preinitiative: median 1 day, mean rank of onset to reporting 47.4, vs postinitiative: median 1 day, mean rank of onset to reporting 35.99, P=.03). The risk-level subgroup analysis found that the onset-to-reporting time for low- and high-risk studies significantly decreased postinitiative (preinitiative: median 4 days, mean rank of low-risk studies 18.73, vs postinitiative: median 1 day, mean rank of low-risk studies 11.76, P=.02; and preinitiative: median 1 day, mean rank of high-risk studies 117.36, vs postinitiative: median 1 day, mean rank of high-risk studies 97.27, P=.01). In particular, onset to reporting was reduced more in the low-risk trial than in the high-risk trial (low-risk: median 4-0 days, vs high-risk: median 1-1 day).
We demonstrated that a real-time automatic alert system can effectively improve safety reporting timelines. The improvements were prominent in phase 1 and in low- and high-risk clinical trials. These findings suggest that an information technology-driven automatic alert system effectively improves safety reporting timelines, which may enhance patient safety.
在临床试验期间尽早发现或通报不良事件(AE)的发生对于确保患者安全至关重要。临床试验利用创新策略、临床设计和先进技术来评估疗效和安全性,然而,研究人员对AE发生的早期认知仍需系统地改进。
本研究旨在构建一个系统,当临床试验参与者不定期前往急诊室或医院内其他科室就诊时,能迅速通知研究人员。
我们开发了不良事件预警系统(AEAS),当研究参与者不定期前往我们中心的急诊科或其他诊所就诊时,该系统会自动发送短信,迅速将AE的发生情况通知研究人员和研究协调员。我们于2015年7月在临床试验管理系统中建立了AEAS。我们比较了74项临床试验中305起AE发生情况在启动前时期(2014年12月至2015年6月)和启动后时期(2015年7月至2016年6月)的AE报告时间线数据,涉及三个AE认知绩效指标:发生至认知、认知至报告以及发生至报告。
共纳入了74项临床试验的305份初始AE报告。启动后时期所有三个AE认知绩效指标均显著降低。具体而言,启动后时期的发生至报告时间显著短于启动前时期(中位数1天[四分位间距0 - 1],平均秩次140.04[标准差75.35]),而启动前时期为(中位数1天[四分位间距0 - 4],平均秩次173.82[标准差91.07],P≤.001)。在阶段亚组分析中,1期研究的认知至报告和发生至报告指标在启动后时期显著低于启动前时期(启动前:中位数1天,认知至报告的平均秩次47.94,与启动后:中位数0天,认知至报告的平均秩次35.75,P = 0.01;启动前:中位数1天,发生至报告的平均秩次47.4,与启动后:中位数1天,发生至报告的平均秩次35.99,P = 0.03)。风险水平亚组分析发现,低风险和高风险研究的发生至报告时间在启动后显著缩短(启动前:中位数4天,低风险研究的平均秩次18.73,与启动后:中位数1天,低风险研究的平均秩次11.76,P = 0.02;启动前:中位数1天,高风险研究的平均秩次117.36,与启动后:中位数1天,高风险研究的平均秩次97.27,P = 0.01)。特别是,低风险试验中发生至报告的缩短幅度大于高风险试验(低风险:中位数4 - 0天,与高风险:中位数1 - 1天)。
我们证明了实时自动警报系统可有效改善安全报告时间线。在1期以及低风险和高风险临床试验中改进尤为显著。这些发现表明,信息技术驱动的自动警报系统可有效改善安全报告时间线,这可能会提高患者安全性。