Enhancing diversity to reduce health information disparities and build an evidence base for genomic medicine
Open accessAbstract
Advances in genomic medicine are arising from efforts to build a national learning healthcare system (LHS) and large-scale precision medicine studies. However, the underlying evidence base lacks sufficient data from populations historically underrepresented in biomedical research. Although the literature on health and healthcare disparities is extensive, disparities in the availability and quality of health information about diverse and underrepresented populations are less well characterized. This Perspective describes scientific and ethical benefits to incorporating health information from diverse and underrepresented populations in the LHS, resulting in a more robust and generalizable LHS. Near-term recommendations for incorporating diversity into the evidence base for genomic medicine are proposed, even as the groundwork for national and international efforts is underway.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
There is inadequate collection of socio-economic and demographic information and historic under-representation in EHRs and research among some communities.
“Furthermore, less reliance on formal care for PLWD among some communities [69], inadequate collection of socio-economic and demographic information and historic under-representation in EHRs and research among some communities [70], means true prevalence among certain population groups may not be discovered [71].”
From The Impact of demographic, socio-economic and geographic factors on mortality risk among people living with dementia in England (2002–2016) (2021) · cites this paper as [70]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
The FAIR Guiding Principles for scientific data management and stewardship
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., Blomberg, N., Boiten, J.-W., da Silva Santos, L. B., Bourne, P. E., et al. (2016) · Scientific Data · doi:10.1038/sdata.2016.18 · Cited by 18,423 · see citing works
The Association of American Medical Colleges
ZAPFFE, F. C. (1938) · Academic Medicine · doi:10.1097/00001888-193801000-00007 · Cited by 5,527 · see citing works
A New Initiative on Precision Medicine
Collins, F. S., & Varmus, H. (2015) · New England Journal of Medicine · doi:10.1056/nejmp1500523 · Cited by 5,202 · see citing works
Genomics is failing on diversity
Popejoy, A. B., & Fullerton, S. M. (2016) · Nature · doi:10.1038/538161a · Cited by 1,924 · see citing works
Best care at lower cost: the path to continuously learning health care in America
Smith, M. A., Saunders, R., Stuckhardt, L., & McGinnis, J. M. (2014) · Choice Reviews Online · doi:10.5860/choice.51-3277 · Cited by 1,356 · see citing works
Million Veteran Program: A mega-biobank to study genetic influences on health and disease
Gaziano, J. M., Concato, J., Brophy, M., Fiore, L., Pyarajan, S., Breeling, J., Whitbourne, S., Deen, J., Shannon, C., Humphries, D., et al. (2016) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.09.016 · Cited by 1,055 · see citing works
Design and Implementation of the Hispanic Community Health Study / Study of Latinos
Sorlie, P., Avilés-Santa, L. M., Wassertheil-Smoller, S., Kaplan, R., Daviglus, M., Giachello, A., Schneiderman, N., Raij, L., Talavera, G., Allison, M., et al. (2010) · Annals of Epidemiology · doi:10.1016/j.annepidem.2010.03.015 · Cited by 830 · see citing works
Genetic Misdiagnoses and the Potential for Health Disparities
Manrai, A. K., Funke, B. H., Rehm, H. L., Olesen, M. S., Maron, B. A., Szolovits, P., Margulies, D. M., Loscalzo, J., & Kohane, I. S. (2016) · New England Journal of Medicine · doi:10.1056/nejmsa1507092 · Cited by 808 · see citing works
Assessing the Gold Standard — Lessons from the History of RCTs
Bothwell, L. E., Greene, J. A., Podolsky, S. H., & Jones, D. S. (2016) · New England Journal of Medicine · doi:10.1056/nejmms1604593 · Cited by 664 · see citing works
THE STRONG HEART STUDY A STUDY OF CARDIOVASCULAR DISEASE IN AMERICAN INDIANS: DESIGN AND METHODS
Lee, E. T., Welty, T. K., Fabsitz, R. R., Cowan, L. D., Le, N., Oopik, A. J., Cucchiara, A. J., Savage, P. J., & Howard, B. V. (1990) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a115757 · Cited by 613 · see citing works
The PCORI Perspective on Patient-Centered Outcomes Research
Frank, L. B., Basch, E., & Selby, J. V. (2014) · JAMA · doi:10.1001/jama.2014.11100 · Cited by 585 · see citing works
Preemptive Clinical Pharmacogenetics Implementation: Current Programs in Five US Medical Centers
Dunnenberger, H. M., Crews, K. R., Hoffman, J. M., et al. (2014) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010814-124835 · Cited by 514 · see citing works
Friedman, C., Rubin, J., Brown, J., Buntin, M., Corn, M., Etheredge, L., Gunter, C., Musen, M., Platt, R., Stead, W., et al. (2015) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2014-002977 · Cited by 509 · see citing works
Chen, M. S., Lara, P. N., Dang, J. H. T., Paterniti, D. A., & Kelly, K. L. (2014) · Cancer · doi:10.1002/cncr.28575 · Cited by 477 · see citing works
Addressing social determinants of health and health inequalities
Adler, N. E., Glymour, M. M., & Fielding, J. (2016) · JAMA · doi:10.1001/jama.2016.14058 · Cited by 426 · see citing works
The National Academies of Sciences, Engineering and Medicine
(2020) · Palgrave Macmillan UK eBooks · doi:10.1057/978-1-349-95988-4_100311 · Cited by 370 · see citing works
Epigenetics and Human DiseasePreprint
Zoghbi, H. Y., & Beaudet, A. L. (2016) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a019497 · Cited by 361 · see citing works
Landry, L. G., Ali, N., Williams, D. R., Rehm, H. L., & Bonham, V. L. (2018) · Health Affairs · doi:10.1377/hlthaff.2017.1595 · Cited by 344 · see citing works
Chambers, D. A., Feero, W. G., & Khoury, M. J. (2016) · JAMA · doi:10.1001/jama.2016.3867 · Cited by 313 · see citing works
Petrovski, S., & Goldstein, D. B. (2016) · Genome Biology · doi:10.1186/s13059-016-1016-y · Cited by 255 · see citing works
Sanderson, S. C., Brothers, K. B., Mercaldo, N. D., Clayton, E. W., Antommaria, A. H. M., Aufox, S. A., Brilliant, M. H., Campos, D., Carrell, D., Connolly, J. J., et al. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.01.021 · Cited by 241 · see citing works
Morales, J., Welter, D., Bowler, E. H., Cerezo, M., Harris, L. W., McMahon, A. C., Hall, P., Junkins, H. A., Milano, A., Hastings, E., et al. (2018) · Genome Biology · doi:10.1186/s13059-018-1396-2 · Cited by 217 · see citing works
Self-citationZhang, X., Pérez‐Stable, E. J., Bourne, P. E., Peprah, E. K., Duru, O. K., Breen, N., Berrigan, D. A., Wood, F. B., Jackson, J. S., Wong, D. W. S., et al. (2017) · Ethnicity & Disease · doi:10.18865/ed.27.2.95 · Cited by 194 · see citing works
Optimizing Drug Outcomes Through Pharmacogenetics: A Case for Preemptive Genotyping
Schildcrout, J. S., Denny, J. C., Bowton, E., Gregg, W., Pulley, J. M., Basford, M., Cowan, J. D., Xu, H., Ramirez, A. H., Crawford, D. C., et al. (2012) · Clinical Pharmacology & Therapeutics · doi:10.1038/clpt.2012.66 · Cited by 192 · see citing works
Fisher, E. S., Shortell, S. M., & Savitz, L. A. (2016) · JAMA · doi:10.1001/jama.2015.17949 · Cited by 192 · see citing works
Weinfurt, K. P., Hernandez, A. F., Coronado, G. D., DeBar, L., Dember, L. M., Green, B. B., Heagerty, P. J., Huang, S. S., James, K. T., Jarvik, J. G., et al. (2017) · BMC Medical Research Methodology · doi:10.1186/s12874-017-0420-7 · Cited by 183 · see citing works
Achieving Equity in an Evolving Healthcare System: Opportunities and Challenges
Williams, J. S., Walker, R. J., & Egede, L. E. (2016) · The American Journal of the Medical Sciences · doi:10.1016/j.amjms.2015.10.012 · Cited by 177 · see citing works
Shabani, M., & Borry, P. (2017) · European Journal of Human Genetics · doi:10.1038/s41431-017-0045-7 · Cited by 173 · see citing works
Landry, L. G., & Rehm, H. L. (2018) · JAMA Cardiology · doi:10.1001/jamacardio.2017.5333 · Cited by 110 · see citing works
From Evidence Based Medicine to Medicine Based Evidence
Horwitz, R. I., Conroy, A. H., Caricchio, R., & Singer, B. H. (2017) · The American Journal of Medicine · doi:10.1016/j.amjmed.2017.06.012 · Cited by 108 · see citing works
Mapping Neighborhood Health Geomarkers To Clinical Care Decisions To Promote Equity In Child Health
Beck, A. F., Sandel, M. T., Ryan, P., & Kahn, R. S. (2017) · Health Affairs · doi:10.1377/hlthaff.2016.1425 · Cited by 105 · see citing works
Shirts, B. H., Salama, J. S., Aronson, S., et al. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv065 · Cited by 96 · see citing works
Biases introduced by filtering electronic health records for patients with “complete data.”
Weber, G. M., Adams, W. G., Bernstam, E. V., Bickel, J. P., Fox, K. P., Marsolo, K., Raghavan, V. A., Turchin, A., Zhou, X., Murphy, S. N., et al. (2017) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocx071 · Cited by 93 · see citing works
Some experiences and opportunities for big data in translational research
Chute, C. G., Ullman-Culleré, M., Wood, G. M., Lin, S. M., He, M., & Pathak, J. (2013) · Genetics in Medicine · doi:10.1038/gim.2013.121 · Cited by 83 · see citing works
Wang, S., Jiang, X., Singh, S., Marmor, R., Bonomi, L., Fox, D., Dow, M., & Ohno‐Machado, L. (2017) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.13259 · Cited by 78 · see citing works
Changes in Demographics of Patients Seen at Federally Qualified Health Centers, 2005-2014
Nath, J. B., Costigan, S., & Hsia, R. Y.-J. (2016) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2016.0705 · Cited by 67 · see citing works
Privacy preserving interactive record linkage (PPIRL)
Kum, H., Krishnamurthy, A. K., Machanavajjhala, A., Reiter, M. K., & Ahalt, S. C. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-002165 · Cited by 64 · see citing works
iCONCUR: informed consent for clinical data and bio-sample use for research
Kim, H., Bell, E., Kim, J., Sitapati, A. M., Ramsdell, J., Farcas, C., Friedman, D., Feupe, S. F., & Lucila Ohno-machado, A. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw115 · Cited by 64 · see citing works
The Influence of Big (Clinical) Data and Genomics on Precision Medicine and Drug Development
Denny, J. C., Driest, S. L. V., Wei, W., & Roden, D. M. (2017) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.951 · Cited by 53 · see citing works
Sharing health-related data: a privacy test?
Dyke, S. O. M., Dove, E. S., & Knoppers, B. M. (2016) · npj Genomic Medicine · doi:10.1038/npjgenmed.2016.24 · Cited by 47 · see citing works
Douglas, M. D., Dawes, D. E., Holden, K. B., & Mack, D. (2015) · American Journal of Public Health · doi:10.2105/ajph.2014.302384 · Cited by 45 · see citing works
Ensuring Public Health’s Future in a National-Scale Learning Health System
Bernstein, J. A., Friedman, C. P., Jacobson, P., et al. (2015) · American Journal of Preventive Medicine · doi:10.1016/j.amepre.2014.11.013 · Cited by 44 · see citing works
Race/ethnicity, personal health record access, and quality of care.
Garrido, T., Kanter, M. H., Meng, D., et al. (2015) · PubMed · Cited by 42 · see citing works
Adrift in the gray zone: IRB perspectives on research in the learning health system
Lee, S. S., Kelley, M. C., Cho, M. K., et al. (2016) · AJOB Empirical Bioethics · doi:10.1080/23294515.2016.1155674 · Cited by 35 · see citing works
Stronks, K., Wieringa, N. F., & Hardon, A. P. (2013) · Trials · doi:10.1186/1745-6215-14-177 · Cited by 31 · see citing works
Oreskovic, N. M., Maniates, J., Weilburg, J. B., et al. (2017) · JMIR Medical Informatics · doi:10.2196/medinform.8240 · Cited by 31 · see citing works
'More research needed': plugging gaps in the evidence base on health inequalities
Petticrew, M. P. (2007) · European Journal of Public Health · doi:10.1093/eurpub/ckm094 · Cited by 30 · see citing works
International code of conduct for genomic and health-related data sharing
Regulatory and Ethics Working Group, G. A. F. G. &. H., & Sugano, S. (2014) · The HUGO Journal · doi:10.1186/1877-6566-8-1 · Cited by 27 · see citing works
Lu, C. Y., Williams, M. S., Ginsburg, G. S., Toh, S., Brown, J. S., & Khoury, M. J. (2017) · Genetics in Medicine · doi:10.1038/gim.2017.122 · Cited by 27 · see citing works
Leveraging the learning health care model to improve equity in the age of genomic medicine
Blizinsky, K. D., & Bonham, V. L. (2017) · Learning Health Systems · doi:10.1002/lrh2.10046 · Cited by 27 · see citing works
Self-citationPerfectly Secure and Efficient Two-Party Electronic-Health-Record Linkage
Chen, F., Jiang, X., Wang, S., et al. (2018) · IEEE Internet Computing · doi:10.1109/mic.2018.112102542 · Cited by 27 · see citing works
Hollister, B. M., RESTREPO, N. A., Farber‐Eger, E. H., Crawford, D. C., Aldrich, M. C., & Non, A. L. (2016) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789813207813_0023 · Cited by 26 · see citing works
Nodora, J., Komenaka, I. K., Bouton, M. E., et al. (2016) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djw201 · Cited by 11 · see citing works
IOM Roundtable on the Promotion of Health Equity and the Elimination of Health Disparities
Barclay, G. (2014) · 142nd APHA Annual Meeting and Exposition (November 15 - November 19, 2014) · Cited by 6 · see citing works
INTEGRATING COMMUNITY-LEVEL DATA RESOURCES FOR PRECISION MEDICINE RESEARCH
Bush, W. S., Crawford, D. C., Briggs, F. B. S., Freedman, D. A., & Sloan, C. (2017) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789813235533_0057 · Cited by 3 · see citing works
Flagged first, then by citations
Research works printed but not linked: 3
- [18]Committee on the Recommended Social and Behavioral Domains and Measures for Electronic Health Records, Institute of Medicine. Capturing Social and Behavioral Domains in Electronic Health Records: Phase 1. (2014). 24757748
- [19]Committee on the Recommended Social and Behavioral Domains and Measures for Electronic Health Records, Institute of Medicine. Capturing Social and Behavioral Domains and Measures in Electronic Health Records: Phase 2. (2015). 25590118
- [26]Wojick GG M; Nishimura KK; Tao R; Haessler J; Gignoux CR; Highland HM; Patel YM; Sorokin EP; Avery CL; Belbin GM; Bien SA; Cheng I; Hodonsky CJ; Huckins LM; Jeff J; Justice AE; Kocarnik JM; Lim U; Lin BM; Lu Y; Nelson SC; Park SL; Preuss MH; Richard MA; Schurmann C; Setiawan VW; Vahi K; Vishnu A; Verbanck M; Walker R; Young KL; Zubair N; Ambite JL; Boerwinkle E; Bottinger E; Bustamante CD; Caberto C; Conomos MP; Deelman E; Do R; Doheny K; Fernandez-Rhodes L; Fornage M; Heiss G; Hindorff LA; Jackson RD; James R; Laurie CC; Li Y; Lin D; Nadkarni G; Pooler LC; Reiner AP; Romm J; Sabati C; Sheng X; Stahl E; Stram DO; Thornton TA; Wassel CL; Wilkens LR; Yoneyama S; Buyske S; Haiman C; Kooperberg C; Le Marchand L; Loos R; J.F Matise T.C North K.E Peters U Kenny E.E Carlson C.S. Genetic Diversity Turns a New PAGE in Our Understanding of Complex Traits. Preprint available at https://www.biorxiv.org/content/early/2017/09/15/188094, (2017).
Cited by
Sorted by citations
Morales, A., Kinnamon, D. D., Jordan, E., Platt, J., Vatta, M., Dorschner, M. O., Starkey, C. A., Mead, J. O., Ai, T., Burke, W., et al. (2020) · Circulation: Genomic and Precision Medicine · doi:10.1161/circgen.119.002480 · Cited by 114 · see citing works
Self-citationWatson, J., Darlington-Pollock, F., Green, M., Giebel, C., & Akpan, A. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph182413405 · Cited by 21 · see citing works
- Authors
- Hindorff, L. A., Bonham, V. L., & Ohno-Machado, L.
- Affiliations
- National Institutes of Health (US)
- UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, 92093, USA
- Corresponding author
- Hindorff, Lucia A
- Venue
- Personalized Medicine
- Publisher
- Informa UK Limited
- Published
- 2018-09
- Volume
- 15
- Issue
- 5
- Pages
- 403-412
- ISSN
- 1741-0541 (ISSN-L)
- 1744-828X
- PMC
- PMC6287493
- OpenAlex
- W2891477245
- Cited by
- 58
- References
- 55
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 5 · 2023: 12 · 2022: 6 · 2021: 9 · 2020: 5 · 2019: 11 · 2018: 2 · 2017: 1
- FWCI
- 4.13
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- public-domain
- Locations
- Personalized Medicine (publishedVersion, public-domain)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Health (R01HG008802, OT2OD026552, R01GM118609, R01HL136835, I01HX000982)
- PCORI (CDRN-1306-04819)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Race, Genetics, and Society
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Ethics in Clinical Research
- Social Sciences › Sociology and Political Science › Cultural Competency in Health Care
- Keywords
- genomic medicine, underrepresented groups, diversity in research, learning healthcare systems, precision medicine, evidence base, health information quality, research ethics, generalizability
- MeSH terms
- Ethnicity, Humans, Minority Groups, Patient Education as Topic, Cultural Diversity, Genomics, Healthcare Disparities, Precision Medicine
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 ›
Are you an author, or do you see a problem with this page? Request a review
