{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T01:03:48Z","timestamp":1755219828572,"version":"3.43.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643686080","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,8,7]]},"abstract":"<jats:p>Analyzing medication-related incident reports is crucial for patient safety; however, systematically extracting the underlying factors contributing to incident occurrence remains challenging. We developed a multi-label classifier that automatically identified incident factors from 1,212 drug-related incident reports using the Bidirectional Encoder Representations from Transformers and its derivatives. Based on the P-mSHELL model, a comprehensive framework for incident factor analysis, we established seven distinct factor categories and evaluated various pre-trained models through five-fold cross-validation. Almost all models achieved macro F1 scores exceeding 0.6, with the lightweight A Lite BERT model showing comparable performance to BERT. This study demonstrates the practical feasibility of natural language processing techniques for systematic incident factor analysis, supporting enhanced patient safety management.<\/jats:p>","DOI":"10.3233\/shti250942","type":"book-chapter","created":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:35:52Z","timestamp":1754566552000},"source":"Crossref","is-referenced-by-count":0,"title":["Development of an Automated Classification System for Medication-Related Incident Factors: A Practical Approach to Enhancing Patient Safety Management"],"prefix":"10.3233","author":[{"given":"Yuri","family":"Takamatsu","sequence":"first","affiliation":[{"name":"Division of Drug Informatics, Keio University Faculty of Pharmacy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sayaka","family":"Ebara","sequence":"additional","affiliation":[{"name":"Division of Drug Informatics, Keio University Faculty of Pharmacy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4572-1333","authenticated-orcid":false,"given":"Hayato","family":"Kizaki","sequence":"additional","affiliation":[{"name":"Division of Drug Informatics, Keio University Faculty of Pharmacy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Satoshi","family":"Watabe","sequence":"additional","affiliation":[{"name":"Division of Drug Informatics, Keio University Faculty of Pharmacy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5706-613X","authenticated-orcid":false,"given":"Shungo","family":"Imai","sequence":"additional","affiliation":[{"name":"Division of Drug Informatics, Keio University Faculty of Pharmacy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6209-1054","authenticated-orcid":false,"given":"Shuntaro","family":"Yada","sequence":"additional","affiliation":[{"name":"Institute of Library, Information and Media Science, University of Tsukuba"},{"name":"Division of Information Science, Nara Institute of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0201-3609","authenticated-orcid":false,"given":"Eiji","family":"Aramaki","sequence":"additional","affiliation":[{"name":"Division of Information Science, Nara Institute of Science and Technology"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-8861-9279","authenticated-orcid":false,"given":"Osamu","family":"Yasumuro","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, Kameda General Hospital"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1897-9689","authenticated-orcid":false,"given":"Ryohkan","family":"Funakoshi","sequence":"additional","affiliation":[{"name":"Department of Pharmacy, Kameda General Hospital"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4596-5418","authenticated-orcid":false,"given":"Satoko","family":"Hori","sequence":"additional","affiliation":[{"name":"Division of Drug Informatics, Keio University Faculty of Pharmacy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Studies in Health Technology and Informatics","MEDINFO 2025 \u2014 Healthcare Smart \u00d7 Medicine Deep"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/SHTI250942","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T11:35:52Z","timestamp":1754566552000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/SHTI250942"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9781643686080"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/shti250942","relation":{},"ISSN":["0926-9630","1879-8365"],"issn-type":[{"value":"0926-9630","type":"print"},{"value":"1879-8365","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,8,7]]}}}