Koh Jodie, Caron Stacey, Watters Amber N, Vaidyanathan Mahesh, Melnick David, Santi Alyssa, Hudson Kenneth, Arguelles Catherine, Mathur Priyanka, Etemadi Mozziyar
Kellogg School of Management, Northwestern University, Evanston, IL, United States.
Northwestern Medicine, Chicago, IL, United States.
JMIR Form Res. 2025 Jan 29;9:e58628. doi: 10.2196/58628.
Patient recruitment and data management are laborious, resource-intensive aspects of clinical research that often dictate whether the successful completion of studies is possible. Technological advances present opportunities for streamlining these processes, thus improving completion rates for clinical research studies.
This paper aims to demonstrate how technological adjuncts can enhance clinical research processes via automation and digital integration.
Using one clinical research study as an example, we highlighted the use of technological adjuncts to automate and streamline research processes across various digital platforms, including a centralized database of electronic medical records (enterprise data warehouse [EDW]); a clinical research data management tool (REDCap [Research Electronic Data Capture]); and a locally managed, Health Insurance Portability and Accountability Act-compliant server. Eligible participants were identified through automated queries in the EDW, after which they received personalized email invitations with digital consent forms. After digital consent, patient data were transferred to a single Health Insurance Portability and Accountability Act-compliant server where each participant was assigned a unique QR code to facilitate data collection and integration. After the research study visit, data obtained were associated with existing electronic medical record data for each participant via a QR code system that collated participant consent, imaging data, and associated clinical data according to a unique examination ID.
Over a 19-month period, automated EDW queries identified 20,988 eligible patients, and 10,582 patients received personalized email invitations. In total, 1000 (9.45%) patients signed consents to participate in the study. Of the consented patients, 549 unique patients completed 779 study visits; some patients consented to the study at more than 1 time period during their pregnancy.
Technological adjuncts in clinical research decrease human labor while increasing participant reach and minimizing disruptions to clinic operations. Automating portions of the clinical research process benefits clinical research efforts by expanding and optimizing participant reach while reducing the limitations of labor and time in completing research studies.
患者招募和数据管理是临床研究中费力且资源密集的环节，往往决定着研究能否成功完成。技术进步为简化这些流程提供了机会，从而提高临床研究的完成率。
本文旨在展示技术辅助手段如何通过自动化和数字整合来优化临床研究流程。
以一项临床研究为例，我们重点介绍了如何利用技术辅助手段在多个数字平台上自动化和简化研究流程，这些平台包括电子病历集中数据库（企业数据仓库[EDW]）、临床研究数据管理工具（REDCap[研究电子数据采集]）以及本地管理的符合《健康保险流通与责任法案》的服务器。通过在EDW中进行自动查询来识别符合条件的参与者，之后他们会收到带有数字同意书的个性化电子邮件邀请。获得数字同意后，患者数据被传输到一个符合《健康保险流通与责任法案》的单一服务器，为每位参与者分配一个唯一的二维码，以方便数据收集和整合。在研究访视后，通过二维码系统将获取的数据与每位参与者现有的电子病历数据相关联，该系统根据唯一的检查ID整理参与者的同意书、影像数据及相关临床数据。
在19个月的时间里，EDW自动查询识别出20988名符合条件的患者，10582名患者收到了个性化电子邮件邀请。共有1000名（9.45%）患者签署同意书参与研究。在签署同意书的患者中，549名不同患者完成了779次研究访视；一些患者在孕期的多个时间段同意参与研究。
临床研究中的技术辅助手段减少了人力，同时扩大了参与者范围，并将对临床运营的干扰降至最低。临床研究过程的部分自动化有利于临床研究工作，通过扩大和优化参与者范围减少了完成研究的人力和时间限制。
