Publication | Open Access
The <i>All of Us</i> Research Program: data quality, utility, and diversity
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2020
Year
Unknown Venue
EngineeringEhr SystemsDatabasesData CurationPopulation Health SciencesHealth DisparitiesHealth StudiesCardiovascular Disease ScoreProspective Cohort StudyData ScienceDigital HealthPublic HealthData ManagementStatisticsHealth PolicyBiobehavioral HealthData QualityCohort StudyResearch Data ManagementElectronic Health RecordResearch Data ArchivingClinical DataPrecision MedicineHealth Data ScienceHealth Information TechnologyOncologic AssociationsHealth DataData LiteracyHealth Informatics
Abstract Importance The All of Us Research Program hypothesizes that accruing one million or more diverse participants engaged in a longitudinal research cohort will advance precision medicine and ultimately improve human health. Launched nationally in 2018, to date All of Us has recruited more than 345,000 participants. All of Us plans to open beta access to researchers in May 2020. Objective To demonstrate the quality, utility, and diversity of the All of Us Research Program’s initial data release and beta launch of the cloud-based analysis platform, the cloud-based Researcher Workbench. Evidence We analyzed the initial All of Us data release, comprising surveys, physical measurements (PM), and electronic health record (EHR) data, to characterize All of Us participants including self-reported descriptors of diversity. Data depth, density, and quality were evaluated using medication sequencing analyses for depression and type 2 diabetes. Replication of known oncologic associations with smoking exposure ascertained by EHR and survey data and calculation of population-based atherosclerotic cardiovascular disease risk scores demonstrated the utility of data and platform capability. Findings The beta launch of the All of Us Researcher Workbench contains data on 224,143 participants. Seventy-seven percent of this cohort were identified as Underrepresented in Biomedical Research (UBR) including over forty-eight percent self-reporting non-White race. Medication usage patterns in common diseases depression and type 2 diabetes replicated prior findings previously reported in the literature and showed differences based on race. Oncologic associations with smoking were replicated and effect sizes compared for EHR and survey exposures finding general agreement. A cardiovascular disease score was calculated utilizing multiple data elements curated across sources. The cloud-based architecture built in the Researcher Workbench provided secure access and powerful computational resources at a low cost. All analyses have been made available for replication and reuse by registered researchers. Conclusions and Relevance The All of Us Research Program’s initial release of cohort data contains longitudinal and multidimensional data on diverse participants that replicate known associations. This dataset and the cloud-based Researcher Workbench advance the mission of All of Us to make data widely and securely available to researchers to improve human health and advance precision medicine.
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