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The “All of Us” Research Program
Author(s) -
Joshua C. Denny
Publication year - 2019
Publication title -
new england journal of medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 19.889
H-Index - 1030
eISSN - 1533-4406
pISSN - 0028-4793
DOI - 10.1056/nejmsr1809937
Subject(s) - observational study , diversity (politics) , health equity , medical education , protocol (science) , socioeconomic status , health records , research program , medicine , data collection , gerontology , data science , family medicine , psychology , alternative medicine , health care , environmental health , computer science , public health , population , nursing , political science , law , philosophy , statistics , mathematics , epistemology , pathology
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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