The All of Us Research Program: data quality, utility, and diversity
Authors: Ramirez Andrea H. , Sulieman Lina , Schlueter David J. , Halvorson Alese , Qian Jun , Ratsimbazafy Francis , Loperena Roxana , Mayo Kelsey , Basford Melissa , Deflaux Nicole , Muthuraman Karthik N. , Natarajan Karthik , Kho Abel , Xu Hua , Wilkins Consuelo , Anton-Culver Hoda , Boerwinkle Eric , Cicek Mine , Clark Cheryl R. , Cohn Elizabeth , Ohno-Machado Lucila , Schully Sheri , Ahmedani Brian K. , Argos Maria , Cronin Robert M. , O’Donnell Christopher , Fouad Mona , Goldstein David B. , Greenland Philip , Hebbring Scott J. , Karlson Elizabeth W. , Khatri Parinda , Korf Bruce , Smoller Jordan W. , Sodeke Stephen , Wilbanks John , Hentges Justin , Lunt Christopher , Devaney Stephanie A. , Gebo Kelly , C Denny Joshua , Carroll Robert J. , Glazer David , Harris Paul A. , Hripcsak George , Philippakis Anthony , Roden Dan M. 
Published: June 2020

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.