{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T16:37:50Z","timestamp":1785602270700,"version":"3.56.0"},"reference-count":20,"publisher":"Oxford University Press (OUP)","issue":"3","license":[{"start":{"date-parts":[[2021,12,13]],"date-time":"2021-12-13T00:00:00Z","timestamp":1639353600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000266","name":"Engineering and Physical Sciences Research Council","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100000266","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Centre for Doctoral Training in Cloud Computing for Big Data, Newcastle University","award":["EP\/L015358\/1"],"award-info":[{"award-number":["EP\/L015358\/1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,1,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Primary care EHR data are often of clinical importance to cohort studies however they require careful handling. Challenges include determining the periods during which EHR data were collected. Participants are typically censored when they deregister from a medical practice, however, cohort studies wish to follow participants longitudinally including those that change practice. Using UK Biobank as an exemplar, we developed methodology to infer continuous periods of data collection and maximize follow-up in longitudinal studies. This resulted in longer follow-up for around 40% of participants with multiple registration records (mean increase of 3.8\u00a0years from the first study visit). The approach did not sacrifice phenotyping accuracy when comparing agreement between self-reported and EHR data. A diabetes mellitus case study illustrates how the algorithm supports longitudinal study design and provides further validation. We use UK Biobank data, however, the tools provided can be used for other conditions and studies with minimal alteration.<\/jats:p>","DOI":"10.1093\/jamia\/ocab260","type":"journal-article","created":{"date-parts":[[2021,11,23]],"date-time":"2021-11-23T12:15:05Z","timestamp":1637669705000},"page":"546-552","source":"Crossref","is-referenced-by-count":28,"title":["Curating a longitudinal research resource using linked primary care EHR data\u2014a UK Biobank case study"],"prefix":"10.1093","volume":"29","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9033-2767","authenticated-orcid":false,"given":"Philip","family":"Darke","sequence":"first","affiliation":[{"name":"School of Computing, Newcastle University, Newcastle upon Tyne, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0228-7274","authenticated-orcid":false,"given":"Sophie","family":"Cassidy","sequence":"additional","affiliation":[{"name":"Central Clinical School, The University of Sydney, Sydney, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Catt","sequence":"additional","affiliation":[{"name":"Population Health Sciences Institute, Newcastle University, Newcastle upon Tyne, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roy","family":"Taylor","sequence":"additional","affiliation":[{"name":"Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Paolo","family":"Missier","sequence":"additional","affiliation":[{"name":"School of Computing, Newcastle University, Newcastle upon Tyne, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2692-7205","authenticated-orcid":false,"given":"Jaume","family":"Bacardit","sequence":"additional","affiliation":[{"name":"School of Computing, Newcastle University, Newcastle upon Tyne, 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