{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"medRxiv"}],"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T19:48:50Z","timestamp":1774640930578,"version":"3.50.1"},"posted":{"date-parts":[[2026,3,24]]},"group-title":"Health Informatics","reference-count":28,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T00:00:00Z","timestamp":1774310400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,3,25]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:sec>\n                  <jats:title>Background<\/jats:title>\n                  <jats:p>Open health data repositories receive billions in public funding, yet no systematic framework exists to evaluate their downstream scholarly impact, the composition of the research communities they cultivate, or the breadth of disciplines they reach. We introduce a two-degree citation methodology to quantify knowledge diffusion from open data, normalized by funding, and apply it to four major health data repositories.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>\n                    Using the OpenAlex bibliometric database (January\u2013February 2026), we identified all first-degree citing publications (\n                    <jats:italic>n<\/jats:italic>\n                    = 30,049) and their second-degree citing publications (\n                    <jats:italic>n<\/jats:italic>\n                    = 485,396), defined as papers citing those first-degree publications, for MIMIC (versions I\u2013 IV; retrospective EHR data; $14.4M), UK Biobank (prospective cohort with genomics; $525.5M), OpenSAFELY (federated EHR platform; $53.7M), and All of Us (prospective national cohort with biobanking and community engagement; $2,160M). We extracted author demographics (gender via Genderize.io, institutional country income via World Bank 2024 classifications) and research topics. Chi-square tests with odds ratios assessed demographic differences across repositories.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>\n                    Funding-normalized first-degree papers per $1M ranged from 689 (MIMIC) to 1 (All of Us), though these figures reflect total program investment, which included community engagement and biobanking for prospective cohorts in addition to data-curation costs. The citation amplification ratio was consistent across these four repositories (9.3\u201311.5\u00d7). Author demographics differed significantly (\n                    <jats:italic>p &lt;<\/jats:italic>\n                    0.001): LMIC authorship ranged from 41.8% (MIMIC) to 4.3% (All of Us), while female authorship showed the opposite pattern, lowest for MIMIC (31.8%) and highest for All of Us (43.2%). Female authors were consistently underrepresented in senior (last-author) compared with first-author positions across all repositories. Differences in scope, design, and what funding covers limit direct comparisons.\n                  <\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Conclusions<\/jats:title>\n                  <jats:p>Open health data generates a consistent \u223c10\u00d7 indirect citation amplification beyond its direct users, a ratio that held across repositories spanning over two orders of magnitude in funding. The large differences in funding-normalized output partly reflect structural differences between retrospective databases and prospective cohorts. Low-cost access combined with intentional community building attracted globally diverse research communities with LMIC investigators in intellectual leadership positions, while a persistent gender gap in senior authorship across all repositories reflects disciplinary and structural inequities that data access policies alone cannot address. Future evaluations of open data investments should examine who is producing research, from where, in what positions, and whether their participation translates into locally relevant knowledge production.<\/jats:p>\n                <\/jats:sec>\n                <jats:sec>\n                  <jats:title>Take-home message<\/jats:title>\n                  <jats:p>Open health data shows a consistent \u223c10\u00d7 citation amplification ratio beyond direct users. Low-barrier access and active community-building are associated with globally diverse research communities, including LMIC researchers in leadership positions, yet representational equity in authorship does not guarantee locally relevant knowledge production. A persistent gender gap in senior authorship across all repositories reflects disciplinary and structural inequities that data access policies alone cannot address.<\/jats:p>\n                <\/jats:sec>","DOI":"10.64898\/2026.03.20.26348933","type":"posted-content","created":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T23:20:11Z","timestamp":1774394411000},"source":"Crossref","is-referenced-by-count":0,"title":["The Power of Open Health Data: Impact, Representation, and Knowledge Diffusion"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4386-957X","authenticated-orcid":false,"given":"Rahul","family":"Gorijavolu","sequence":"first","affiliation":[{"name":"Artificial Intelligence for Responsible, Generalizable, and Open Surgical (ARGOS) Research Group, Baltimore, MD, USA"},{"name":"Laboratory for Computational Physiology, MIT Critical Data, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"name":"Johns Hopkins University School of Medicine, Baltimore, MD, USA"},{"name":"Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7012-2973","authenticated-orcid":false,"given":"Miguel \u00c1ngel","family":"Armengol de la Hoz","sequence":"additional","affiliation":[{"name":"Big Data Department, PMC, Fundaci\u00f3n Progreso y Salud, Seville, Spain"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1871-3909","authenticated-orcid":false,"given":"Catherine","family":"Bielick","sequence":"additional","affiliation":[{"name":"Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0579-6178","authenticated-orcid":false,"given":"Sebastian","family":"Cajas","sequence":"additional","affiliation":[{"name":"Laboratory for Computational Physiology, MIT Critical Data, Massachusetts Institute of Technology, Cambridge, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5786-2627","authenticated-orcid":false,"given":"Marie-Laure","family":"Charpignon","sequence":"additional","affiliation":[{"name":"Institute for Data, Systems, and Society, Massachusetts Institute of Technology, Cambridge, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8274-3340","authenticated-orcid":false,"given":"Aya","family":"El Mir","sequence":"additional","affiliation":[{"name":"Department of Machine Learning, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1097-316X","authenticated-orcid":false,"given":"Judy W.","family":"Gichoya","sequence":"additional","affiliation":[{"name":"Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0847-5073","authenticated-orcid":false,"given":"Hyunjung Gloria","family":"Kwak","sequence":"additional","affiliation":[{"name":"Nell Hodgson Woodruff School of Nursing, Emory University, Atlanta, GA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4248-6519","authenticated-orcid":false,"given":"Kaushik","family":"Madapati","sequence":"additional","affiliation":[{"name":"Artificial Intelligence for Responsible, Generalizable, and Open Surgical (ARGOS) Research Group, Baltimore, MD, USA"},{"name":"Laboratory for Computational Physiology, MIT Critical Data, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"name":"College of Engineering, University of California, Berkeley, CA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1263-2537","authenticated-orcid":false,"given":"Heather","family":"Mattie","sequence":"additional","affiliation":[{"name":"Harvard T.H. Chan School of Public Health, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9788-7987","authenticated-orcid":false,"given":"Lucas","family":"McCullum","sequence":"additional","affiliation":[{"name":"UT MD Anderson Cancer Center UTHealth Houston Graduate School of Biomedical Sciences, Houston, TX, USA"},{"name":"Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-2994-7182","authenticated-orcid":false,"given":"Rogers","family":"Mwavu","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Mbarara University of Science and Technology, Mbarara, Uganda"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-3999-9913","authenticated-orcid":false,"given":"Vishnu","family":"Nair","sequence":"additional","affiliation":[{"name":"Johns Hopkins University School of Medicine, Baltimore, MD, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6847-6748","authenticated-orcid":false,"given":"Luis Filipe","family":"Nakayama","sequence":"additional","affiliation":[{"name":"Laboratory for Computational Physiology, MIT Critical Data, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"name":"Ophthalmology Department, Escola Paulista de Medicina, Universidade de S\u00e3o Paulo, S\u00e3o Paulo, SP, Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-4547-3319","authenticated-orcid":false,"given":"Josephine","family":"Nanyonjo","sequence":"additional","affiliation":[{"name":"Health Informatics Equity Lab, School of Nursing, Faculty of Health and Social Development, University of British Columbia Okanagan, Kelowna, BC, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7550-4751","authenticated-orcid":false,"given":"Lama","family":"Nazer","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, King Hussein Cancer Center, Amman, Jordan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9179-267X","authenticated-orcid":false,"given":"Milit S.","family":"Patel","sequence":"additional","affiliation":[{"name":"Laboratory for Computational Physiology, MIT Critical Data, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"name":"Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2388-5919","authenticated-orcid":false,"given":"Christopher M.","family":"Sauer","sequence":"additional","affiliation":[{"name":"Laboratory for Computational Physiology, MIT Critical Data, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"name":"Department of Hematology and Stem Cell Transplantation, University Hospital Essen, Essen, Germany"},{"name":"Institute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6712-6626","authenticated-orcid":false,"given":"Leo A.","family":"Celi","sequence":"additional","affiliation":[{"name":"Laboratory for Computational Physiology, MIT Critical Data, Massachusetts Institute of Technology, Cambridge, MA, USA"},{"name":"Division of Pulmonary, Critical Care and Sleep Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA"},{"name":"Department of Biostatistics, Harvard T.H. 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