创新的受试者招聘系统用于批次招聘的应用:试点研究
Chung-Il Wi1,2, Katherine S King3, Euijung Ryu2,4
1Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN, USA.
Journal of primary care & community health
|August 30, 2023
概括
使用技术支持的受试者招聘系统 (TESRS) 进行自动批量招聘,可显著加快临床试验招聘,并降低员工负担. 这种数字化方法提高了效率,同时确保了参与者的多样化代表性,使其成为未来研究的宝贵工具.
科学领域:
- 临床试验 临床试验
- 医疗信息学 医疗信息学
- 生物医学研究生物医学研究
背景情况:
- 传统的临床试验招生面临着效率和参与者代表性方面的挑战.
- 电子健康记录 (EHR) 提供了简化招聘流程的潜力.
- 数字技术可以解决受试者招募中的低效率问题.
研究的目的:
- 评估基于技术的受试者招聘系统 (TESRS) 的有效性,用于自动批次招生.
- 在招聘速度,员工时间和参与者人口统计学方面,比较TESRS与传统的邮寄方法.
- 确定TESRS是否提高了招聘,同时保持研究对象的代表性.
主要方法:
- 一项基于社区的前性成年人队列研究随机选择了600名符合条件的受试者.
- 研究对象被分配到TESRS (n=300) 或标准邮件 (n=300) 中3个月.
- TESRS利用电子健康记录来了解患者的联系偏好,自动邀请,在线调查和数字同意,并对同意时间,招聘人数,员工时间和社会人口统计代表性进行比较.
主要成果:
- 与标准邮件 (11%) 相比,TESRS在3个月内实现了类似的同意率 (13%).
- 使用TESRS (中位数7天) 的招聘速度明显快于使用标准邮件 (中位数26天).
- 据估计,TESRS为每个受试者节省了大约40分钟的研究人员时间,并且在参与者的社会人口统计特征上没有显著差异.
结论:
- TESRS是一种有价值的数字招聘技术,可以显著提高招聘效率.
- 该系统减少了与参与者招聘相关的研究人员负担.
- TESRS保持了被招募受试者的特征的一致性,支持其在不同学习环境中的实施.
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