{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T17:59:11Z","timestamp":1792432751614,"version":"4.5.0"},"reference-count":30,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2022,11,1]],"date-time":"2022-11-01T00:00:00Z","timestamp":1667260800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000272","name":"National Institute for Health Research","doi-asserted-by":"publisher","award":["NIHR 203986"],"award-info":[{"award-number":["NIHR 203986"]}],"id":[{"id":"10.13039\/501100000272","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Journal of Multimorbidity and Comorbidity"],"published-print":{"date-parts":[[2022,11]]},"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Structured Medication Reviews (SMRs) are intended to help deliver the NHS Long Term Plan for medicines optimisation in people living with multiple long-term conditions and polypharmacy. It is challenging to gather the information needed for these reviews due to poor integration of health records across providers and there is little guidance on how to identify those patients most urgently requiring review.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>To extract information from scattered clinical records on how health and medications change over time, apply interpretable artificial intelligence (AI) approaches to predict risks of poor outcomes and overlay this information on care records to inform SMRs. We will pilot this approach in primary care prescribing audit and feedback systems, and co-design future medicines optimisation decision support systems.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Design<\/jats:title>\n                    <jats:p>DynAIRx will target potentially problematic polypharmacy in three key multimorbidity groups, namely, people with (a) mental and physical health problems, (b) four or more long-term conditions taking ten or more drugs and (c) older age and frailty. Structured clinical data will be drawn from integrated care records (general practice, hospital, and social care) covering an \u223c11m population supplemented with Natural Language Processing (NLP) of unstructured clinical text. AI systems will be trained to identify patterns of conditions, medications, tests, and clinical contacts preceding adverse events in order to identify individuals who might benefit most from an SMR.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>By implementing and evaluating an AI-augmented visualisation of care records in an existing prescribing audit and feedback system we will create a learning system for medicines optimisation, co-designed throughout with end-users and patients.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/26335565221145493","type":"journal-article","created":{"date-parts":[[2022,12,15]],"date-time":"2022-12-15T23:53:42Z","timestamp":1671148422000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":21,"title":["The DynAIRx Project Protocol: Artificial Intelligence for dynamic prescribing optimisation and care integration in multimorbidity"],"prefix":"10.1177","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3827-4387","authenticated-orcid":false,"given":"Lauren E","family":"Walker","sequence":"first","affiliation":[{"name":"Wolfson Centre for Personalized Medicine, University of Liverpool, Liverpool, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aseel S","family":"Abuzour","sequence":"additional","affiliation":[{"name":"Academic Unit for Ageing & Stroke Research, University of Leeds, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Danushka","family":"Bollegala","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Liverpool, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew","family":"Clegg","sequence":"additional","affiliation":[{"name":"Academic Unit for Ageing & Stroke Research, University of Leeds, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark","family":"Gabbay","sequence":"additional","affiliation":[{"name":"Institute of Population Health, University of Liverpool, Liverpool, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alan","family":"Griffiths","sequence":"additional","affiliation":[{"name":"Public Advisor"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cecil","family":"Kullu","sequence":"additional","affiliation":[{"name":"Mersey Care NHS Foundation Trust, Liverpool, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gary","family":"Leeming","sequence":"additional","affiliation":[{"name":"Civic Data Cooperative, University of Liverpool, Liverpool, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9780-1135","authenticated-orcid":false,"given":"Frances S","family":"Mair","sequence":"additional","affiliation":[{"name":"General Practice and Primary Care, School of Health and Wellbeing, University of Glasgow, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Simon","family":"Maskell","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering, Electronics and Computer Science, University of Liverpool, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Samuel","family":"Relton","sequence":"additional","affiliation":[{"name":"Institute of Health Sciences, University of Leeds, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roy A","family":"Ruddle","sequence":"additional","affiliation":[{"name":"School of Computing and Leeds Institute for Data Analytics, University of Leeds, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eduard","family":"Shantsila","sequence":"additional","affiliation":[{"name":"Institute of Population Health, University of Liverpool, Liverpool, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthew","family":"Sperrin","sequence":"additional","affiliation":[{"name":"Division of Informatics, Imaging & Data Sciences, University of Manchester, Manchester, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tjeerd","family":"Van Staa","sequence":"additional","affiliation":[{"name":"Division of Informatics, Imaging & Data Sciences, University of Manchester, Manchester, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alan","family":"Woodall","sequence":"additional","affiliation":[{"name":"Directorate of Mental Health and Learning Disabilities, Powys Teaching Health Board, Bronllys, 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