The “All of Us” Research Program
Open accessAbstract
Knowledge gained from observational cohort studies has dramatically advanced the prevention and treatment of diseases. Many of these cohorts, however, are small, lack diversity, or do not provide comprehensive phenotype data. The All of Us Research Program plans to enroll a diverse group of at least 1 million persons in the United States in order to accelerate biomedical research and improve health. The program aims to make the research results accessible to participants, and it is developing new approaches to generate, access, and make data broadly available to approved researchers. All of Us opened for enrollment in May 2018 and currently enrolls participants 18 years of age or older from a network of more than 340 recruitment sites. Elements of the program protocol include health questionnaires, electronic health records (EHRs), physical measurements, the use of digital health technology, and the collection and analysis of biospecimens. As of July 2019, more than 175,000 participants had contributed biospecimens. More than 80% of these participants are from groups that have been historically underrepresented in biomedical research. EHR data on more than 112,000 participants from 34 sites have been collected. The All of Us data repository should permit researchers to take into account individual differences in lifestyle, socioeconomic factors, environment, and biologic characteristics in order to advance precision diagnosis, prevention, and treatment.
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The All of Us Research Program has enrolled about 400,000 diverse participants of the 1 million people planned across the USA, and is focused on enrolling individuals from broadly defined underrepresented groups in biomedical research.
“The All of Us Research Program 90 constitutes another novel and ambitious initiative by the NIH that has enrolled about 400,000 diverse participants of the 1 million people planned across the USA, and is focused on enrolling individuals from broadly defined underrepresented groups in biomedical research, which is especially needed in medical AI 91,92 .”
From Multimodal biomedical AI (2022) · cites this paper as [90]
The Abstract states a goal of enrolling at least 1 million people in the United States, and PARTICIPANT CHARACTERISTICS describes a broad focus on groups underrepresented in biomedical research. But CURRENT STATUS OF THE PROGRAM reports more than 230,000 total participants as of July 2019, not about 400,000; the cited paper does not support that enrollment figure. (LLM, conf=0.92)
Experimental — accuracy not yet measuredThe All of Us Research Program is accumulating multiple streams of health-related information in 1,000,000 or more Americans and includes a focus on populations usually under-represented in biomedical research.
“The All of Us Research Program (AoURP) is an initiative that is accumulating multiple streams of health-related information (for example, electronic health records (EHRs), genomics, physical measures, participant surveys and wearables such as Fitbit) in 1,000,000 or more Americans and includes a focus on populations usually under-represented in biomedical research to date8.”
From Association of step counts over time with the risk of chronic disease in the All of Us Research Program (2022) · cites this paper as [8]
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- Authors
- The All of Us Research Program Investigators
- Affiliations
- Broad Institute (US)
- Corresponding author
- The All of Us Research Program Investigators
- Venue
- New England Journal of Medicine
- Publisher
- Massachusetts Medical Society
- Published
- 2019-08-15
- Volume
- 381
- Issue
- 7
- Pages
- 668-676
- ISSN
- 0028-4793 (ISSN-L)
- 1533-4406
- PMC
- PMC8291101
- OpenAlex
- W4205170775
- Cited by
- 2,440
- References
- 35
- Citations by year
- 2026: 544 · 2025: 566 · 2024: 473 · 2023: 301 · 2022: 251 · 2021: 171 · 2020: 112 · 2019: 19 · 2017: 2 · 2012: 1
- FWCI
- 127.32
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- other-oa
- Locations
- New England Journal of Medicine (publishedVersion, other-oa)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Massachusetts General Hospital
- Vanderbilt University
- Vanderbilt University Medical Center
- Broad Institute
- National Institutes of Health (OT2OD026557, OT2OD025277, 1ot2od025285-01, OT2OD025315, OT2OD025337, OT2OD023132, U24OD023121, OT2OD023205, OT2OD026556, U24OD023176, OT2OD026549, OT2OD026553, OT2OD026555, U2COD023196, OT2OD026554, OT2OD026550, OT2OD026548, OT2OD026551, U24OD023163, OT2OD026552, OT2OD023206, OT2OD025276)
- Irving Medical Center, Columbia University
- National Cancer Institute (P30CA013148)
- National Institute of Environmental Health Sciences (P30ES027792)
- National Center for Advancing Translational Sciences
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Health, Environment, Cognitive Aging
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Keywords
- All of Us, large-scale cohort study, participant recruitment, health data repositories, electronic health records, biospecimen collection, digital health technologies, health data sharing, underrepresented populations in research, precision medicine
- MeSH terms
- Health Surveys, Humans, Research Design, United States, Cohort Studies, Biological Specimen Banks, Biomedical Research, Precision Medicine, Electronic Health Records, Observational Studies as Topic, Datasets as Topic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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