退伍军人健康管理局远程数字健康研究的招募与留存结果:多中心观察性研究
Enrollment and Retention Outcomes from the Veterans Health Administration for a Remote Digital Health Study: Multisite Observational Study.
作者信息
Pagliaro Jaclyn A, Wash Lauren K, Ly Ka, Mathew Jenny, Leibowitz Alison, Cabrera Ryan, Wormwood Jolie B, Vimalananda Varsha G
机构信息
Center for Health Optimization and Implementation Research, VA Bedford Medical Center, Bedford, MA, United States.
Neurological Clinical Research Institute, Massachusetts General Hospital, Boston, MA, United States.
出版信息
JMIR Form Res. 2025 Aug 15;9:e68676. doi: 10.2196/68676.
BACKGROUND
Clinical trials of remote patient monitoring (RPM) technology are well-suited to remote studies, for which patients complete key procedures online. However, remote digital health studies often suffer from low enrollment and retention, threatening the successful achievement of study outcomes and wasting resources and time. Recruiting patients from a large integrated health system offers a greater potential pool of participants for enrollment, which can increase the likelihood of successful study completion.
OBJECTIVE
This study describes enrollment and retention outcomes for a remote digital health study of an RPM device conducted in collaboration with researchers from the Veterans Health Administration (VA). The VA is the largest integrated health system in the United States, with 9 million enrollees who are, as a group, older and with more medical and mental health comorbidities than the civilian population.
METHODS
We aimed to enroll 200 VA patients for a clinical study of a cellular-enabled, handheld, multisensor device that captures multiple health parameters and transmits data to a cloud-based dashboard for viewing by clinicians. Eligible patients were hospitalized with COVID-19 within 3-6 months before enrollment and had one of 6 pre-existing medical comorbidities. Potentially eligible patients were identified using the VA Corporate Data Warehouse. Every 3 weeks, up to 1000 potentially eligible patients were mailed a recruitment letter. All study tasks, including obtaining informed consent, device training and troubleshooting, and handling study-related questions, were completed online and by telephone. Device and survey data were combined with VA clinical and utilization data to develop a predictive algorithm for clinical decompensation. The geographic distribution of enrolled patients was mapped by county. Demographic and health characteristics of nonenrolled versus enrolled, and of completers versus noncompleters were compared using t tests and chi-square tests as appropriate. Reasons for noncompletion were summed. Multivariate logistic regression was used to evaluate variables associated with enrolling versus nonenrolling, and completing versus noncompleting.
RESULTS
Of the 7714 who were mailed a study invitation, 560 were screened. Of the screened patients, 203 were enrolled (2.9% enrollment yield) and 166 completed the study (82% retention rate). Enrolled patients were broadly distributed across the United States. Among those enrolled, completers and noncompleters were similar except for a slightly higher proportion of patients with hypertension among completers. The most common reason for noncompletion of the study was that participants were unable to be contacted for study tasks.
CONCLUSIONS
Remote digital health studies are increasingly common, but inadequate enrollment often results in failed studies. Recruiting patients through the VA enables access to a very large population of potentially eligible patients and can help ensure that clinical trials reach targets for enrollment and completion.
TRIAL REGISTRATION
ClinicalTrials.gov NCT05713266; https://clinicaltrials.gov/study/NCT05713266.
背景
远程患者监测(RPM)技术的临床试验非常适合远程研究,此类研究中患者可在线完成关键程序。然而,远程数字健康研究常常面临招募率低和留存率低的问题,这威胁到研究结果的成功达成,还会浪费资源和时间。从大型综合医疗系统招募患者能提供更大的潜在参与者库,从而增加研究成功完成的可能性。
目的
本研究描述了一项与退伍军人健康管理局(VA)的研究人员合作开展的关于RPM设备的远程数字健康研究的招募和留存结果。VA是美国最大的综合医疗系统,有900万参保者,作为一个群体,他们比普通人群年龄更大,有更多的医疗和心理健康合并症。
方法
我们旨在招募200名VA患者参与一项关于一款支持蜂窝网络的手持式多传感器设备的临床研究,该设备可捕获多个健康参数并将数据传输到基于云的仪表板供临床医生查看。符合条件的患者在入组前3至6个月内因COVID-19住院,且患有6种预先存在的医疗合并症之一。利用VA企业数据仓库识别潜在符合条件的患者。每3周向多达1000名潜在符合条件的患者邮寄一封招募信。所有研究任务,包括获得知情同意、设备培训与故障排除以及处理与研究相关的问题,均通过在线和电话方式完成。将设备和调查数据与VA临床和使用数据相结合,以开发一种用于临床失代偿的预测算法。按县绘制入组患者的地理分布。使用t检验和卡方检验(视情况而定)比较未入组与入组患者以及完成研究与未完成研究患者的人口统计学和健康特征。汇总未完成研究的原因。使用多变量逻辑回归评估与入组与否以及完成研究与否相关的变量。
结果
在收到研究邀请的7714人中,560人接受了筛查。在接受筛查的患者中,203人入组(招募率为2.9%),166人完成了研究(留存率为82%)。入组患者广泛分布于美国各地。在入组患者中,完成研究的患者和未完成研究的患者相似,只是完成研究的患者中高血压患者的比例略高。未完成研究最常见的原因是无法联系到参与者进行研究任务。
结论
远程数字健康研究越来越普遍,但招募不足往往导致研究失败。通过VA招募患者能够接触到大量潜在符合条件的患者,并有助于确保临床试验达到招募和完成目标。
试验注册
ClinicalTrials.gov NCT05713266;https://clinicaltrials.gov/study/NCT05713266
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