Building a Digital Health Research Platform to Enable Recruitment, Enrollment, Data Collection, and Follow-Up for a Highly Diverse Longitudinal US Cohort of 1 Million People in the All of Us Research Program: Design and Implementation Study

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Bibliografiset tiedot
Julkaisussa:Journal of Medical Internet Research vol. 27 (2025), p. e60189
Päätekijä: Klein, Dave
Muut tekijät: Montgomery, Aisha, Begale, Mark, Sutherland, Scott, Sawyer, Sherilyn, McCauley, Jacob L, Husbands, Letheshia, Joshi, Deepti, Ashbeck, Alan, Palmer, Marcy, Jain, Praduman
Julkaistu:
Gunther Eysenbach MD MPH, Associate Professor
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024 7 |a 10.2196/60189  |2 doi 
035 |a 3222368449 
045 2 |b d20250101  |b d20251231 
100 1 |a Klein, Dave 
245 1 |a Building a Digital Health Research Platform to Enable Recruitment, Enrollment, Data Collection, and Follow-Up for a Highly Diverse Longitudinal US Cohort of 1 Million People in the All of Us Research Program: Design and Implementation Study 
260 |b Gunther Eysenbach MD MPH, Associate Professor  |c 2025 
513 |a Journal Article 
520 3 |a Background:Longitudinal cohort studies have traditionally relied on clinic-based recruitment models, which limit cohort diversity and the generalizability of research outcomes. Digital research platforms can be used to increase participant access, improve study engagement, streamline data collection, and increase data quality; however, the efficacy and sustainability of digitally enabled studies rely heavily on the design, implementation, and management of the digital platform being used.Objective:We sought to design and build a secure, privacy-preserving, validated, participant-centric digital health research platform (DHRP) to recruit and enroll participants, collect multimodal data, and engage participants from diverse backgrounds in the National Institutes of Health’s (NIH) All of Us Research Program (AOU). AOU is an ongoing national, multiyear study aimed to build a research cohort of 1 million participants that reflects the diversity of the United States, including minority, health-disparate, and other populations underrepresented in biomedical research (UBR).Methods:We collaborated with community members, health care provider organizations (HPOs), and NIH leadership to design, build, and validate a secure, feature-rich digital platform to facilitate multisite, hybrid, and remote study participation and multimodal data collection in AOU. Participants were recruited by in-person, print, and online digital campaigns. Participants securely accessed the DHRP via web and mobile apps, either independently or with research staff support. The participant-facing tool facilitated electronic informed consent (eConsent), multisource data collection (eg, surveys, genomic results, wearables, and electronic health records [EHRs]), and ongoing participant engagement. We also built tools for research staff to conduct remote participant support, study workflow management, participant tracking, data analytics, data harmonization, and data management.Results:We built a secure, participant-centric DHRP with engaging functionality used to recruit, engage, and collect data from 705,719 diverse participants throughout the United States. As of April 2024, 87% (n=613,976) of the participants enrolled via the platform were from UBR groups, including racial and ethnic minorities (n=282,429, 46%), rural dwelling individuals (n=49,118, 8%), those over the age of 65 years (n=190,333, 31%), and individuals with low socioeconomic status (n=122,795, 20%).Conclusions:We built a participant-centric digital platform with tools to enable engagement with individuals from different racial, ethnic, and socioeconomic backgrounds and other UBR groups. This DHRP demonstrated successful use among diverse participants. These findings could be used as best practices for the effective use of digital platforms to build and sustain cohorts of various study designs and increase engagement with diverse populations in health research. 
653 |a Socioeconomic status 
653 |a Software development 
653 |a Collaboration 
653 |a Genomics 
653 |a Ethnic groups 
653 |a Cohort analysis 
653 |a Software upgrading 
653 |a Efficacy 
653 |a Best practice 
653 |a Data collection 
653 |a Multimodality 
653 |a Leadership 
653 |a Research methodology 
653 |a Clinical outcomes 
653 |a Minority groups 
653 |a Data quality 
653 |a Recruitment 
653 |a Multisource 
653 |a Informed consent 
653 |a Computer platforms 
653 |a Medical research 
653 |a Generalizability 
653 |a Low income groups 
653 |a Computerized medical records 
653 |a Medical personnel 
653 |a Harmonization 
653 |a Tracking 
653 |a Privacy 
653 |a Health records 
653 |a Literacy 
653 |a Health insurance 
653 |a Medical records 
653 |a Management 
653 |a Research design 
653 |a Health care industry 
653 |a Health research 
653 |a Enrollments 
653 |a Institutes 
653 |a Implementation 
653 |a Ethnicity 
653 |a Health services 
653 |a Software 
653 |a Biomedicine 
700 1 |a Montgomery, Aisha 
700 1 |a Begale, Mark 
700 1 |a Sutherland, Scott 
700 1 |a Sawyer, Sherilyn 
700 1 |a McCauley, Jacob L 
700 1 |a Husbands, Letheshia 
700 1 |a Joshi, Deepti 
700 1 |a Ashbeck, Alan 
700 1 |a Palmer, Marcy 
700 1 |a Jain, Praduman 
773 0 |t Journal of Medical Internet Research  |g vol. 27 (2025), p. e60189 
786 0 |d ProQuest  |t Library Science Database 
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