The All of Us Research Program, powered by Vibrent’s Digital Health Research Platform (DHRP), addressed key challenges in traditional research methods—such as low diversity, high dropout rates, and fragmented data collection. By enabling participation through sites, community and internet, multimodal data integrations (EHRs, wearables, genomics, patient generated data), and automated workflows, the program enrolled over 848,000 participants with 87% from underrepresented groups. Through an engaging, consumer-friendly UI, Vibrent’s platform enhanced participant engagement and retention, reduced inequalities, reduced costs, and significantly increased efficiency, thus setting a new standard for large-scale health studies.
Key Barriers and Limitations of Traditional Research Models and Technologies
Manual Processes & High Costs
Recruitment & Diversity Gaps
Geographic Barriers for Rural Participation
Engagement & Retention
Data Fragmentation & Siloed Workstreams
Many Vendor Contracts
Timeline Delays
Site-Only, High Patient Burden
Where Vibrent Came In
Initial Deployment
(2017)
Developed for large-scale hybrid and decentralized approach and to address inefficiencies in traditional research methods.
National Launch
(May 2018)
Nationwide US launch with Vibrent as the technology backbone.
Expansion & Scaling
(2019-2020)
Scaled to 100k+ participants, integrating multi-source data from the clinic and real-world data sources.
Ongoing Enhancements
(2021-present)
Scaled to support 1 MILLION people and AI automation.
Vibrent’s Key Impact
Increased Diversity and Inclusion in Research Participation
With AI-powered outreach and multichannel recruitment (site-based, digital, and community-based), Underrepresented Group (UBR) participation rose to 87%, far exceeding the traditional <10%.
Enabled the inclusion of diverse populations, 58,000 rural participants, 52,000 sexual and gender minorities, and other historically underrepresented groups (100k Black, 25k Asian, 55k Multi-race).
Large Scale Enrollment, Engagement, and Retention
848,783 participants enrolled.
Multiple languages.
Retention rates increased to 74% long-term, compared to the typical 56% in traditional studies.
Automated engagement workflows reduced dropout rates and increased participant follow-through.
Expanded Multimodal Data Collection
Remotely collected over 1,000 TB including ePROs, surveys, EHRs, genomics results, biospecimens, SDoH, wearables, and remote cognitive assessments.
Improved Compliance & Data Security
Vibrent’s platform is HIPAA, GDPR, SOC2 Type 2, and Cyber Essentials compliant and Ethics, HRA, NHS DTAC ready.
Automated tracking and audit systems ensured regulatory adherence.
Data Integration & Real-time Analytics
Vibrent integrated wearables, biospecimens, and real-time EHR data, which were not supported by traditional platforms like REDCap.
This integration eliminated data silos, enabling more effective research.
Study Timeline & Cost Efficiencies
Study start-up times reduced from months to weeks.
Enrollment time reduced by 80%, and recruitment costs reduced by 500%.
Reduced cost per patient referral by 64%.
Researchers gained immediate access to real-time participant data.
• Automation workflows reduced study staff burden by 80%, saving 624 hours per study staff annually.
Scalablility & Decentralisation
Hybrid model combines sites, communities and internet based remote patient experiences.
“Thank you for your contributions throughout the years and for your commitment to diverse representation in research. You have helped make a difference for future generations!”
“You centered your efforts on meaningful support for diverse participant communities. You introduced critical tools like CATI, engagement logs, and customized workflows that served organizations across varied needs, languages, and backgrounds.”
“We are at the anniversary of pulling off something extraordinary—designing, building, and launching pediatric enrollment in less than 1 year’s time. Your team’s hard work, grit, creativity, and expertise made it possible.”
“This program has been a success that exceeds anything like this that the NIH has attempted. I will be forever grateful for your contribution.”
