The All of Us Research Program (All of Us) is a national effort to accelerate health research by exploring the relationship between lifestyle, environment, and genetics. It is set to become one of the largest research efforts in U.S. history, aiming to build a national resource of data from at least one million participants. All of Us aims to address the need for more diversity in research and set the stage for that diversity to be leveraged in precision medicine research to come. This paper describes how the program assessed demographic characteristics of participants who have enrolled in other U.S. biomedical research cohorts to better understand which groups are traditionally represented or underrepresented in biomedical research. We 1) reviewed the enrollment characteristics of national cohort studies like All of Us, and 2) surveyed the literature, focusing on key diversity categories essential to the program's enrollment aims. Based on these efforts, All of Us emphasizes enrollment of racial and ethnic minorities, and has formally designated the following additional groups as historically underrepresented: individuals-with inadequate access to medical care; under the age of 18 or over 65; with an annual household income at or below 200% of the federal poverty level; who have a cognitive or physical disability; have less than a high school education or equivalent; are intersex; identify as a sexual or gender minority; or live in rural or non-metropolitan areas. Research accounting for wider demographic variability is critical. Only by ensuring diversity and by addressing the very barriers that limit it, can we position All of Us to better understand and tackle health disparities.

There is growing public demand that research participants receive all their results regardless of whether clinical action is indicated. Instead of the standard practice of returning only actionable results, we propose a reconceptualization called “return of value” to encompass the varied ways in which research participants value specific results and more general information they receive beyond actionable results. Our proposal is supported by a national survey of a diverse sample, which found that receiving research results would be valuable to most (78.5%) and would make them more likely to trust researchers (70.3%). Respondents highly valued results revealing genetic effects on medication response and predicting disease risk as well as information about nearby clinical trials and updates on how their data was used. The information most valued varied by education, race/ethnicity, and age. Policies are needed to enable return of information in ways that recognize participants’ differing informational needs and values.

The research assessments described in this manuscript were approved by the Institutional Review Board (IRB) of the All of Us Research Program. Those participants that completed cognitive interview gave oral consent to do so.

Objective A participant’s medical history is important in clinical research and can be captured from electronic health records (EHRs) and self-reported surveys. Both can be incomplete, EHR due to documentation gaps or lack of interoperability and surveys due to recall bias or limited health literacy. This analysis compares medical history collected in the All of Us Research Program through both surveys and EHRs. Materials and Methods The All of Us medical history survey includes self-report questionnaire that asks about diagnoses to over 150 medical conditions organized into 12 disease categories. In each category, we identified the 3 most and least frequent self-reported diagnoses and retrieved their analogues from EHRs. We calculated agreement scores and extracted participant demographic characteristics for each comparison set. Results The 4th All of Us dataset release includes data from 314 994 participants; 28.3% of whom completed medical history surveys, and 65.5% of whom had EHR data. Hearing and vision category within the survey had the highest number of responses, but the second lowest positive agreement with the EHR (0.21). The Infectious disease category had the lowest positive agreement (0.12). Cancer conditions had the highest positive agreement (0.45) between the 2 data sources. Discussion and Conclusion Our study quantified the agreement of medical history between 2 sources—EHRs and self-reported surveys. Conditions that are usually undocumented in EHRs had low agreement scores, demonstrating that survey data can supplement EHR data. Disagreement between EHR and survey can help identify possible missing records and guide researchers to adjust for biases.

The 61 CTSA Consortium sites are home to valuable programs and infrastructure supporting translational science and all are charged with ensuring that such investments translate quickly to improved clinical care. CATCHR (Catalog of Assets for Translational and Clinical Health Research) is the Consortium’s effort to collect and make available information on programs and resources to maximize efficiency and facilitate collaborations. By capturing information on a broad range of assets supporting the entire clinical and translational research spectrum, CATCHR aims to provide the necessary infrastructure and processes to establish and maintain an open-access, searchable database of consortium resources to support multi-site clinical and translational research studies. Data is collected using rigorous, defined methods, with the resulting information made visible through an integrated, searchable web-based tool. Additional easy to use web tools assist resource owners in validating and updating resource information over time. In this article, we discuss the design and scope of the project, data collection methods, current results, and future plans for development and sustainability. With increasing pressure on research programs to avoid redundancy, CATCHR aims to make available information on programs and core facilities to maximize efficient use of resources.

In response to the rapidly evolving COVID-19 pandemic, the All of Us Research Program longitudinal cohort study developed the COVID-19 Participant Experience (COPE) survey to better understand the pandemic experiences and health impacts of COVID-19 on diverse populations within the United States. Six survey versions were deployed between May 2020 and March 2021 covering mental health, loneliness, activity, substance use, and discrimination, as well as COVID-19 symptoms, testing, treatment, and vaccination. A total of 104,910 All of Us Research Program participants, of whom over 73% were from communities traditionally underrepresented in biomedical research, completed 275,201 surveys; 9,693 completed all six surveys. Response rates varied widely among demographic groups and were lower among participants from certain racial and ethnic minority populations, participants with low income or educational attainment, and participants with a Spanish language preference. Survey modifications improved participant response rates between the first and last surveys (13.9% to 16.1%, p < 0.001). This paper describes a dataset with longitudinal COVID-19 survey data in a large, diverse population that will enable researchers to address important questions related to the pandemic, a dataset which is of additional scientific value when combined with the program's other data sources.

Objective The All of Us Research Program collects data from multiple information sources, including health surveys, to build a national longitudinal research repository that researchers can use to advance precision medicine. Missing survey responses pose challenges to study conclusions. We describe missingness in All of Us baseline surveys. Study design and setting We extracted survey responses between May 31, 2017, to September 30, 2020. Missing percentages for groups historically underrepresented in biomedical research were compared to represented groups. Associations of missing percentages with age, health literacy score, and survey completion date were evaluated. We used negative binomial regression to evaluate participant characteristics on the number of missed questions out of the total eligible questions for each participant. Results The dataset analyzed contained data for 334,183 participants who submitted at least one baseline survey. Almost all (97.0%) of the participants completed all baseline surveys, and only 541 (0.2%) participants skipped all questions in at least one of the baseline surveys. The median skip rate was 5.0% of the questions, with an interquartile range (IQR) of 2.5% to 7.9%. Historically underrepresented groups were associated with higher missingness (incidence rate ratio (IRR) [95% CI]: 1.26 [1.25, 1.27] for Black/African American compared to White). Missing percentages were similar by survey completion date, participant age, and health literacy score. Skipping specific questions were associated with higher missingness (IRRs [95% CI]: 1.39 [1.38, 1.40] for skipping income, 1.92 [1.89, 1.95] for skipping education, 2.19 [2.09–2.30] for skipping sexual and gender questions). Conclusion Surveys in the All of Us Research Program will form an essential component of the data researchers can use to perform their analyses. Missingness was low in All of Us baseline surveys, but group differences exist. Additional statistical methods and careful analysis of surveys could help mitigate challenges to the validity of conclusions.

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