{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T07:35:19Z","timestamp":1776065719853,"version":"3.50.1"},"reference-count":62,"publisher":"Oxford University Press (OUP)","issue":"8-9","license":[{"start":{"date-parts":[[2019,7,2]],"date-time":"2019-07-02T00:00:00Z","timestamp":1562025600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"name":"Atrius Health and the Center for Population Health IT"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,8,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Geriatric syndromes such as functional disability and lack of social support are often not encoded in electronic health records (EHRs), thus obscuring the identification of vulnerable older adults in need of additional medical and social services. In this study, we automatically identify vulnerable older adult patients with geriatric syndrome based on clinical notes extracted from an EHR system, and demonstrate how contextual information can improve the process.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Materials and Methods<\/jats:title>\n                  <jats:p>We propose a novel end-to-end neural architecture to identify sentences that contain geriatric syndromes. Our model learns a representation of the sentence and augments it with contextual information: surrounding sentences, the entire clinical document, and the diagnosis codes associated with the document. We trained our system on annotated notes from 85 patients, tuned the model on another 50 patients, and evaluated its performance on the rest, 50 patients.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Contextual information improved classification, with the most effective context coming from the surrounding sentences. At sentence level, our best performing model achieved a micro-F1 of 0.605, significantly outperforming context-free baselines. At patient level, our best model achieved a micro-F1 of 0.843.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Discussion<\/jats:title>\n                  <jats:p>Our solution can be used to expand the identification of vulnerable older adults with geriatric syndromes. Since functional and social factors are often not captured by diagnosis codes in EHRs, the automatic identification of the geriatric syndrome can reduce disparities by ensuring consistent care across the older adult population.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>EHR free-text can be used to identify vulnerable older adults with a range of geriatric syndromes.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/jamia\/ocz093","type":"journal-article","created":{"date-parts":[[2019,5,17]],"date-time":"2019-05-17T19:14:05Z","timestamp":1558120445000},"page":"787-795","source":"Crossref","is-referenced-by-count":33,"title":["Identifying vulnerable older adult populations by contextualizing geriatric syndrome information in clinical notes of electronic health records"],"prefix":"10.1093","volume":"26","author":[{"given":"Tao","family":"Chen","sequence":"first","affiliation":[{"name":"Center for Language and Speech Processing, Johns Hopkins Whiting School of Engineering, Baltimore, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mark","family":"Dredze","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Johns Hopkins Whiting School of Engineering, Baltimore, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jonathan P","family":"Weiner","sequence":"additional","affiliation":[{"name":"Center for Population Health IT, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hadi","family":"Kharrazi","sequence":"additional","affiliation":[{"name":"Center for Population Health IT, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA"},{"name":"Division of Health Sciences Informatics, Johns Hopkins School of Medicine, Baltimore, Maryland, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2019,7,2]]},"reference":[{"issue":"3","key":"2020110613082925100_ocz093-B1","first-page":"83","article-title":"Geriatric syndromes: medical misnomer or progress in geriatrics?","volume":"61","author":"Olde Rikkert","year":"2003","journal-title":"Neth J Med"},{"issue":"5","key":"2020110613082925100_ocz093-B2","doi-asserted-by":"crossref","first-page":"246","DOI":"10.3928\/01484834-20100217-01","article-title":"Fostering geriatrics in associate degree nursing education: an assessment of current curricula and clinical experiences","volume":"49","author":"Ironside","year":"2010","journal-title":"J Nurs Educ"},{"issue":"5","key":"2020110613082925100_ocz093-B3","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1111\/j.1532-5415.2007.01156.x","article-title":"Geriatric syndromes: clinical, research, and policy implications of a core geriatric concept","volume":"55","author":"Inouye","year":"2007","journal-title":"J Am Geriatr Soc"},{"issue":"7","key":"2020110613082925100_ocz093-B4","doi-asserted-by":"crossref","first-page":"1331","DOI":"10.1111\/jgs.13484","article-title":"Differences in health at age 100 according to sex: population-based cohort study of centenarians using electronic health records","volume":"63","author":"Hazra","year":"2015","journal-title":"J Am Geriatr Soc"},{"key":"2020110613082925100_ocz093-B5","doi-asserted-by":"crossref","first-page":"248.","DOI":"10.1186\/s12877-017-0645-7","article-title":"Comparing clinician descriptions of frailty and geriatric syndromes using electronic health records: a retrospective cohort study","volume":"17","author":"Anzaldi","year":"2017","journal-title":"BMC Geriatr"},{"issue":"8","key":"2020110613082925100_ocz093-B6","doi-asserted-by":"crossref","first-page":"1499","DOI":"10.1111\/jgs.15411","article-title":"The value of unstructured electronic health record data in geriatric syndrome case identification","volume":"66","author":"Kharrazi","year":"2018","journal-title":"J Am Geriatr Soc"},{"issue":"1","key":"2020110613082925100_ocz093-B7","doi-asserted-by":"crossref","first-page":"e13039","DOI":"10.2196\/13039","article-title":"Extraction of geriatric syndromes from electronic health record clinical notes: assessment of statistical natural language processing methods","volume":"7","author":"Chen","year":"2019","journal-title":"JMIR Med Inform"},{"key":"2020110613082925100_ocz093-B8","doi-asserted-by":"crossref","first-page":"j5085.","DOI":"10.1136\/bmj.j5085","article-title":"CONSORT-Equity 2017 extension and elaboration for better reporting of health equity in randomised trials","volume":"359","author":"Welch","year":"2017","journal-title":"BMJ"},{"issue":"9","key":"2020110613082925100_ocz093-B9","doi-asserted-by":"crossref","first-page":"e015815","DOI":"10.1136\/bmjopen-2016-015815","article-title":"When is a randomised controlled trial health equity relevant? 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