{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T06:45:12Z","timestamp":1783579512533,"version":"3.55.0"},"reference-count":17,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T00:00:00Z","timestamp":1775779200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010269","name":"Wellcome Trust","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100010269","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Big Data"],"abstract":"<jats:p>The increasing volume and heterogeneity of patient care data present significant challenges for comprehensive analysis and the generation of insights, particularly in specific areas such as respiratory diseases. Standardizing diverse health data is crucial for enabling large-scale observational research and ensuring data readiness. The Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) provides a widely adopted standard for harmonizing such data. However, evaluating the quality of data transformed into the OMOP CDM format is a critical step before its use in research or clinical decision support. This study evaluates the impact of the OMOP CDM standardization process on generating data quality insights for a respiratory disease dataset. The source dataset was initially paper-based, converted to an electronic format, and translated from French into English. This historical dataset covers the years 2009\u20132023 and contains 108 variables and 2,154 records. The data underwent the standard Extract, Transform, and Load (ETL) process to convert into the OMOP CDM format. Following this transformation, the quality of the resulting OMOP CDM instance was assessed. We utilized the Data Quality Dashboard (DQD) to evaluate the quality of the OMOP CDM database before and after ETL verification. DQD performs validation checks on the data based on key data quality dimensions, including completeness, plausibility, and conformance. Overall, the assessment conducted 2,344 checks, of which 2,269 passed, and 75 failed, resulting in a corrected pass rate of 96% for the Respiratory Diseases Inpatients data before ETL verification. After ETL verification, the assessment conducted 2,374 checks, of which 2,356 passed, and 40 failed, resulting in a 100% corrected pass rate. Standardizing respiratory disease data using the OMOP CDM enabled a structured and transparent evaluation of data quality. Through the application of the DQD, this study demonstrated the utility of OMOP CDM in generating meaningful data quality insights. These findings highlight the model's potential to enhance data readiness and support evidence-based decision-making in respiratory disease management.<\/jats:p>","DOI":"10.3389\/fdata.2026.1744885","type":"journal-article","created":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T04:28:00Z","timestamp":1775795280000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Evaluating the impact of OMOP-CDM on data quality insight generation in respiratory disease management"],"prefix":"10.3389","volume":"9","author":[{"given":"Brenda Mbouamba","family":"Yankam","sequence":"first","affiliation":[{"name":"Douala General Hospital, Data Science Without Borders Project","place":["Douala, Cameroon"]},{"name":"Faculty of Mathematics, University of Bochum","place":["Bochum, Germany"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fankoua Tchaptchet","family":"Luc Baudoin","sequence":"additional","affiliation":[{"name":"Douala General Hospital, Data Science Without Borders Project","place":["Douala, Cameroon"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pauline","family":"Andeso","sequence":"additional","affiliation":[{"name":"African Population and Health Research Center","place":["Nairobi, Kenya"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fran\u00e7ois Anicet","family":"Onana Akoa","sequence":"additional","affiliation":[{"name":"Douala General Hospital, Data Science Without Borders Project","place":["Douala, Cameroon"]},{"name":"School of Health Sciences, Catholic University of Central Africa","place":["Yaounde, Cameroon"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jean Blaise","family":"Ebimbe","sequence":"additional","affiliation":[{"name":"Douala Gynaeco-Obstetric and Pediatric Hospital","place":["Douala, Cameroon"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Miranda","family":"Barasa","sequence":"additional","affiliation":[{"name":"African Population and Health Research Center","place":["Nairobi, Kenya"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mbele","family":"Onana","sequence":"additional","affiliation":[{"name":"Internal Medicine Department, Douala General Hospital","place":["Douala, Cameroon"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samuel","family":"Iddi","sequence":"additional","affiliation":[{"name":"African Population and Health Research Center","place":["Nairobi, Kenya"]},{"name":"Department of Statistics, University of Ghana","place":["Accra, Ghana"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Agnes","family":"Kiragga","sequence":"additional","affiliation":[{"name":"African Population and Health Research Center","place":["Nairobi, Kenya"]},{"name":"Infectious Diseases Institute, College of Health Sciences, Makerere University","place":["Kampala, Uganda"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bertrand Hugo","family":"Mbatchou Ngahane","sequence":"additional","affiliation":[{"name":"Douala General Hospital, Data Science Without Borders Project","place":["Douala, Cameroon"]},{"name":"Faculty of Medicine and Pharmaceutical Sciences, University of Douala","place":["Douala, Cameroon"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"name":"Data Science Without Borders Project","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,4,10]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1329630","DOI":"10.3389\/fdgth.2024.1329630","article-title":"INSPIRE datahub: a pan-African integrated suite of services for harmonising longitudinal population health data using OHDSI tools","volume":"6","author":"Bhattacharjee","year":"2024","journal-title":"Front. Digit. Health"},{"key":"B2","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1186\/s12874-021-01434-3","article-title":"Standardizing registry data to the OMOP Common Data Model: experience from three pulmonary hypertension databases","volume":"21","author":"Biedermann","year":"2021","journal-title":"BMC Med. Res. Methodol."},{"key":"B3","unstructured":"Blacketer\n              C.\n            \n          \n          Data quality check type definitions\n          \n          2024"},{"key":"B4","doi-asserted-by":"publisher","first-page":"11920","DOI":"10.3390\/app112411920","article-title":"Using the data quality dashboard to improve the EHDEN network","volume":"11","author":"Blacketer","year":"2021","journal-title":"Appl. Sci."},{"key":"B5","first-page":"574","article-title":"Observational Health Data Sciences and Informatics (OHDSI): opportunities for observational researchers HHS public access","volume":"216","author":"Hripcsak","year":"2015","journal-title":"Stud. Health Technol. Inform."},{"key":"B6","doi-asserted-by":"publisher","first-page":"18","DOI":"10.13063\/2327-9214.1244","article-title":"A harmonized data quality assessment terminology and framework for the secondary use of electronic health record data","volume":"4","author":"Kahn","year":"2016","journal-title":"eGEMs"},{"key":"B7","doi-asserted-by":"publisher","first-page":"1116682","DOI":"10.3389\/fpubh.2023.1116682","article-title":"Enabling data sharing and utilization for African population health data using OHDSI tools with an OMOP-common data model","volume":"11","author":"Kiwuwa-Muyingo","year":"2023","journal-title":"Front. Public Health"},{"key":"B8","author":"Li","year":"2020"},{"key":"B9","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1055\/s-0037-1617452","article-title":"Towards implementation of OMOP in a German university hospital consortium","volume":"9","author":"Maier","year":"2018","journal-title":"Appl. Clin. Inform."},{"key":"B10","doi-asserted-by":"crossref","unstructured":"Marteau\n              B. L.\n            \n            \n              Hornback\n              A.\n            \n            \n              Zhong\n              Y.\n            \n            \n              Lowson\n              C.\n            \n            \n              Woloff\n              J.\n            \n            \n              Smith\n              B. M.\n            \n          \n          Improving a large healthcare system research data warehouse using OHDSI's data quality dashboard\n          \n          2024","DOI":"10.1109\/BHI62660.2024.10913573"},{"key":"B11","doi-asserted-by":"publisher","first-page":"1423621","DOI":"10.3389\/fdgth.2025.1423621","article-title":"Harmonizing population health data into OMOP common data model: a demonstration using COVID-19 sero-surveillance data from Nairobi Urban Health and Demographic Surveillance System","volume":"7","author":"Ochola","year":"2025","journal-title":"Front. Digit. Health"},{"key":"B12","doi-asserted-by":"publisher","first-page":"ooab001","DOI":"10.1093\/jamiaopen\/ooab001","article-title":"Transforming and evaluating electronic health record disease phenotyping algorithms using the OMOP common data model: a case study in heart failure","volume":"4","author":"Papez","year":"2021","journal-title":"JAMIA Open"},{"key":"B13","doi-asserted-by":"publisher","first-page":"e0266911","DOI":"10.1101\/2021.04.08.21255178","article-title":"Extract, transform, load framework for the conversion of health databases to OMOP","volume":"17","author":"Quiroz","year":"2021","journal-title":"PLoS One"},{"key":"B14","doi-asserted-by":"publisher","first-page":"757","DOI":"10.1055\/s-0041-1732301","article-title":"Transformation of electronic health records and questionnaire data to OMOP CDM: a feasibility study using SG_T2DM dataset","volume":"12","author":"Sathappan","year":"2021","journal-title":"Appl. Clin. Inform."},{"key":"B15","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1093\/jamia\/ocad214","article-title":"European Health Data and Evidence Network\u2014learnings from building out a standardized international health data network","volume":"31","author":"Voss","year":"2024","journal-title":"J. Am. Med. Inform. Assoc."},{"key":"B16","unstructured":"Adoption of the OMOP CDM for cancer research using real-world data: current status and opportunities\n          \n          \n            \n              Wang\n              L.\n            \n            \n              Wen\n              A.\n            \n            \n              Fu\n              S.\n            \n            \n              Ruan\n              X.\n            \n            \n              Huang\n              M.\n            \n            \n              Li\n              R.\n            \n          \n          39228725\n          medRxiv [Preprint]\n          \n          2024"},{"key":"B17","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.ijid.2014.12.039","article-title":"Tackling the tuberculosis epidemic in sub-Saharan Africa - unique opportunities arising from the second European Developing Countries Clinical Trials Partnership (EDCTP) programme 2015-2024","volume":"32","author":"Zumla","year":"2015","journal-title":"Int. J. Infect. Dis."}],"container-title":["Frontiers in Big Data"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fdata.2026.1744885\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T04:28:01Z","timestamp":1775795281000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/fdata.2026.1744885\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,10]]},"references-count":17,"alternative-id":["10.3389\/fdata.2026.1744885"],"URL":"https:\/\/doi.org\/10.3389\/fdata.2026.1744885","relation":{},"ISSN":["2624-909X"],"issn-type":[{"value":"2624-909X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,10]]},"article-number":"1744885"}}