{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T13:11:48Z","timestamp":1789650708519,"version":"4.0.0"},"reference-count":24,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T00:00:00Z","timestamp":1789603200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Digit. Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Incorporating geographically diverse populations into real-world evidence studies is essential for generating globally applicable insights. However, many African healthcare institutions operate highly customized electronic medical record systems that lack interoperability with international data networks. This paper describes a collaborative implementation to transform legacy electronic medical record data into the OMOP Common Data Model at the Joint Clinical Research Centre (JCRC) in Uganda, enabling participation in federated real-world evidence networks.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A tri-partite collaboration was established between JCRC, IQVIA, and Gilead Sciences. The project was executed in three phases: (1) data assessment and architecture design, (2) extract, transform, and load execution and custom terminology mapping, and (3) validation of the transformed data through a cohort characterization study. JCRC's Integrated Clinical Enterprise Application (ICEA) database, containing over 48,000 patient records, was assessed and transformed to OMOP CDM v5.4. Following conversion, a descriptive observational study characterized four cohorts: all patients, people with HIV (PWH), hepatitis B virus (HBV)-infected, and hepatitis C virus (HCV)-infected patients.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The source database comprised 168 tables and 1,894 fields with no standardized medical coding systems \u2014100% custom terminology\u2014 requiring manual mapping. Over 100\u2005h of collaborative mapping achieved 95% data capture for core domains. A total of 48,748unique patients were successfully mapped to the OMOP CDM. The cohort characterization demonstrated the utility of the transformed data, revealing: HIV prevalence of 38.1% (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u200918,588); HBV prevalence of 7.0% (\n                      <jats:italic>n<\/jats:italic>\n                      \u2009=\u20093,423); and no HCV-infected patients identified. People with HIV demonstrated high care engagement (95.9% on antiretroviral therapy, a median of 25 visits per patient over a median follow-up of 7.6 years). Key data gaps included limited documentation of non-communicable diseases and mortality. Critical lessons included the need for detailed column-level data dictionaries and structured capacity building for local OMOP sustainability.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>This collaboration demonstrates that full OMOP CDM implementation is feasible in highly customized data environments when built on a collaborative design that combines local clinical expertise with global technical support. The project successfully positioned JCRC to engage with OHDSI's federated ecosystem and provides a replicable model for other African institutions seeking to generate representative real-world evidence at scale.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fdgth.2026.1907568","type":"journal-article","created":{"date-parts":[[2026,9,17]],"date-time":"2026-09-17T12:53:07Z","timestamp":1789649587000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["From fragmentation to federation: multi-partner OMOP implementation in Uganda enabling global real-world evidence generation"],"prefix":"10.3389","volume":"8","author":[{"given":"Francis","family":"Kanyike","sequence":"first","affiliation":[{"name":"Joint Clinical Research Centre (JCRC)","place":["Kampala, Uganda"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Annet","family":"Nanungi","sequence":"additional","affiliation":[{"name":"Joint 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