Cornelius Victoria R, McDermott Lisa, Forster Alice S, Ashworth Mark, Wright Alison J, Gulliford Martin C
Department of Primary Care and Public Health Sciences, King's College, London, UK.
Imperial Clinical Trials Unit, Imperial College London, 68 Wood Lane, London, W12 7RH, UK.
Trials. 2018 Jun 27;19(1):341. doi: 10.1186/s13063-018-2723-3.
BACKGROUND/AIMS: Use of electronic health records and information technology to deliver more efficient clinical trials is attracting the attention of research funders and researchers. We report on methodological issues and data quality for a comparison of 'automated' and manual (or 'in-practice') methods for recruitment and randomisation in a large randomised controlled trial, with individual patient allocation in primary care.
We conducted a three-arm randomised controlled trial in primary care to evaluate interventions to improve the uptake of invited NHS health checks for cardiovascular risk assessment. Eligible participants were identified using a borough-wide health check management information system. An in-practice recruitment and randomisation method used at 12 general practices required the research team to complete monthly visits to each general practice. For the fully automated method, employed for six general practices, randomisation of eligible participants was performed automatically and remotely using a bespoke algorithm embedded in the health check management information system.
There were 8588 and 4093 participants recruited for the manual and automated methods, respectively. The in-practice method was ready for implementation 3 months sooner than the automated method and the in-practice method allowed for full control and documentation of the randomisation procedure. However the in-practice approach was labour intensive and the requirement for participant records to be stored locally resulted in the loss of data for 10 practice months. No records for participants allocated using the automated method were lost. A fixed-effects meta-analysis showed that effect estimates for the primary outcome were consistent for the two allocation methods.
This trial demonstrated the feasibility of automated recruitment and randomisation methods into a randomised controlled trial performed in primary care. Future research should explore the application of these techniques in other clinical contexts and health care settings.
Current Controlled Trials, ID: ISRCTN42856343 . Registered on 21 March 2013.
背景/目的：利用电子健康记录和信息技术开展更高效的临床试验正吸引着研究资助者和研究者的关注。我们报告了一项大型随机对照试验中“自动化”与手动（或“实际操作中”）招募及随机分组方法比较的方法学问题和数据质量，该试验在初级保健中进行个体患者分配。
我们在初级保健中开展了一项三臂随机对照试验，以评估旨在提高受邀参加国民健康服务（NHS）心血管风险评估健康检查参与率的干预措施。使用全区范围的健康检查管理信息系统识别符合条件的参与者。在12家全科诊所采用的实际操作中招募和随机分组方法要求研究团队每月对每家全科诊所进行访视。对于6家全科诊所采用的完全自动化方法，符合条件的参与者使用嵌入健康检查管理信息系统的定制算法自动且远程地进行随机分组。
分别通过手动和自动化方法招募了8588名和4093名参与者。实际操作中的方法比自动化方法提前3个月准备好实施，且实际操作中的方法允许对随机分组程序进行全面控制和记录。然而，实际操作中的方法劳动强度大，且要求参与者记录本地存储导致10个诊月的数据丢失。使用自动化方法分配的参与者没有记录丢失。固定效应荟萃分析表明，两种分配方法对主要结局的效应估计一致。
该试验证明了在初级保健中进行的随机对照试验中采用自动化招募和随机分组方法的可行性。未来研究应探索这些技术在其他临床背景和医疗保健环境中的应用。
当前受控试验，ID：ISRCTN42856343。于2013年3月21日注册。
