Successful enrollment for a remote digital health study: recruitment from the Veterans Health Administration (Preprint)
Authors: Pagliaro Jaclyn , Wash Lauren , Ly Ka , Leibowitz Alison , Cabrera Ryan , Vimalananda Varsha 
Published: November 2024

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 a 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 that 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 5G-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 prior to enrollment and had one of six 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 non-enrolled vs. enrolled, and of completers vs. non-completers were compared using t-tests and chi-square tests as appropriate. Reasons for non-completion were summed. Multivariate logistic regression was used to evaluate variables associated with enrolling vs. non-enrolling, and completing vs. non-completing.

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 US. Among those enrolled, completers and non-completers were similar except for a slightly higher proportion of patients with hypertension among completers. The most common reason for non-completion of the study was that participants were unable to be contacted for study tasks, and the second most common reason was difficulty with device functionality.

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.

CLINICALTRIAL

ClinicalTrials.gov NCT05713266