{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T09:04:56Z","timestamp":1770714296061,"version":"3.49.0"},"reference-count":46,"publisher":"Oxford University Press (OUP)","issue":"e1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Objective Accurate food adverse sensitivity documentation in electronic health records (EHRs) is crucial to patient safety. This study examined, encoded, and grouped foods that caused any adverse sensitivity in a large allergy repository using natural language processing and standard terminologies.<\/jats:p>\n               <jats:p>Methods Using the Medical Text Extraction, Reasoning, and Mapping System (MTERMS), we processed both structured and free-text entries stored in an enterprise-wide allergy repository (Partners\u2019 Enterprise-wide Allergy Repository), normalized diverse food allergen terms into concepts, and encoded these concepts using the Systematized Nomenclature of Medicine \u2013 Clinical Terms (SNOMED-CT) and Unique Ingredient Identifiers (UNII) terminologies. Concept coverage also was assessed for these two terminologies. We further categorized allergen concepts into groups and calculated the frequencies of these concepts by group. Finally, we conducted an external validation of MTERMS\u2019s performance when identifying food allergen terms, using a randomized sample from a different institution.<\/jats:p>\n               <jats:p>Results We identified 158 552 food allergen records (2140 unique terms) in the Partners repository, corresponding to 672 food allergen concepts. High-frequency groups included shellfish (19.3%), fruits or vegetables (18.4%), dairy (9.0%), peanuts (8.5%), tree nuts (8.5%), eggs (6.0%), grains (5.1%), and additives (4.7%). Ambiguous, generic concepts such as \u201cnuts\u201d and \u201cseafood\u201d accounted for 8.8% of the records. SNOMED-CT covered more concepts than UNII in terms of exact (81.7% vs 68.0%) and partial (14.3% vs 9.7%) matches.<\/jats:p>\n               <jats:p>Discussion Adverse sensitivities to food are diverse, and existing standard terminologies have gaps in their coverage of the breadth of allergy concepts.<\/jats:p>\n               <jats:p>Conclusion New strategies are needed to represent and standardize food adverse sensitivity concepts, to improve documentation in EHRs.<\/jats:p>","DOI":"10.1093\/jamia\/ocv128","type":"journal-article","created":{"date-parts":[[2015,9,18]],"date-time":"2015-09-18T08:28:09Z","timestamp":1442564889000},"page":"e79-e87","source":"Crossref","is-referenced-by-count":22,"title":["Food entries in a large allergy data repository"],"prefix":"10.1093","volume":"23","author":[{"given":"Joseph M.","family":"Plasek","sequence":"first","affiliation":[{"name":"Division of General Internal Medicine and Primary Care, Brigham and Women\u2019s Hospital, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Foster R.","family":"Goss","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine and Clinical Decision Making, Tufts Medical Center, Boston, MA, USA"},{"name":"Department of Emergency Medicine, University of Colorado, Aurora, CO, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kenneth H.","family":"Lai","sequence":"additional","affiliation":[{"name":"Clinical & Quality Analysis, Partners HealthCare System, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jason J.","family":"Lau","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine and Primary Care, Brigham and Women\u2019s Hospital, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Diane L.","family":"Seger,","sequence":"additional","affiliation":[{"name":"Clinical & Quality Analysis, Partners HealthCare System, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kimberly G.","family":"Blumenthal","sequence":"additional","affiliation":[{"name":"Allergy and Immunology, Massachusetts General Hospital, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paige G.","family":"Wickner","sequence":"additional","affiliation":[{"name":"Division of Rheumatology, Immunology, and Allergy, Brigham and Women\u2019s Hospital, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sarah P.","family":"Slight","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine and Primary Care, Brigham and Women\u2019s Hospital, Boston, MA, USA"},{"name":"Division of Pharmacy, School of Medicine, Pharmacy and Health, Durham University, Durham, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Frank Y.","family":"Chang","sequence":"additional","affiliation":[{"name":"Clinical Informatics, Partners eCare, Partners HealthCare System, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Maxim","family":"Topaz","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine and Primary Care, Brigham and Women\u2019s Hospital, Boston, MA, USA"},{"name":"Harvard Medical School, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David W.","family":"Bates","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine and Primary Care, Brigham and Women\u2019s Hospital, Boston, MA, USA"},{"name":"Harvard Medical School, Boston, MA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Zhou","sequence":"additional","affiliation":[{"name":"Division of General Internal Medicine and Primary Care, Brigham and Women\u2019s Hospital, Boston, MA, USA"},{"name":"Clinical Informatics, Partners eCare, Partners HealthCare System, Boston, MA, USA"},{"name":"Harvard Medical 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