Patient Safety Event Analytics: Narrative Mining, Taxonomy Development, and Learning Health System Integration

cirpublications.com-S2rF-1790899045-g364748059 1790899045 Clinical Intelligence Research Press info@cirpublications.com Clinical Intelligence Research Press Journal of Health Informatics and Digital Systems J. Health Inform. Digit. Syst. 3149-8973 2026 6 2 Patient Safety Event Analytics: Narrative Mining, Taxonomy Development, and Learning Health System Integration Andrei Popescu Mihai Ionescu Elena Stan 2026 10.68159/g364748059 https://cirpublications.com/pub/journal/2/article/g364748059 Young IJB, Luz S, Lone N. A systematic review of natural language processing for classification tasks in the field of incident reporting and adverse event analysis. Int J Med Inform. 2019;132:103971. 10.1016/j.ijmedinf.2019.103971 Tabaie A, Sengupta S, Pruitt ZM, Fong A. A natural language processing approach to categorise contributing factors from patient safety event reports. BMJ Health Care Inform. 2023;30(1):e100731. 10.1136/bmjhci-2022-100731 Boxley C, Fujimoto M, Ratwani RM, Fong A. A text mining approach to categorize patient safety event reports by medication error type. Sci Rep. 2023;13:18354. 10.1038/s41598-023-45152-w Fong A, Adams KT, Gaunt MJ, Howe JL, Kellogg KM, Ratwani RM. Identifying health information technology related safety event reports from patient safety event report databases. J Biomed Inform. 2018;86:135-42. 10.1016/j.jbi.2018.09.007 Choudhury A, Asan O. Role of artificial intelligence in patient safety outcomes: systematic literature review. JMIR Med Inform. 2020;8(7):e18599. 10.2196/18599 Ozonoff A, Milliren CE, Fournier K, Welcher J, Landschaft A, Samnaliev M, et al. Electronic surveillance of patient safety events using natural language processing. Health Informatics J. 2022;28(4):14604582221132429. 10.1177/14604582221132429 Enticott J, Braaf S, Johnson A, Jones A, Teede HJ. Learning health systems using data to drive healthcare improvement and impact: a systematic review. BMC Health Serv Res. 2021;21(1):200. 10.1186/s12913-021-06115-7 Bates DW, Singh H. Two decades since To Err Is Human: an assessment of progress and emerging priorities in patient safety. Health Aff (Millwood). 2018;37(11):1736-43. 10.1377/hlthaff.2018.0738 Rajkomar A, Oren E, Chen K, Dai AM, Hajaj N, Hardt M, et al. Scalable and accurate deep learning with electronic health records. NPJ Digit Med. 2018;1:18. 10.1038/s41746-018-0029-1 De Micco F, Di Palma G, Ferorelli D, De Benedictis A, Tomassini L, Tambone V, et al. Artificial intelligence in healthcare: transforming patient safety with intelligent systems-A systematic review. Front Med (Lausanne). 2025;11:1522554. 10.3389/fmed.2024.1522554 Fairie P, Santana MJ, Ahmed S. Categorising patient concerns using natural language processing. BMJ Health Care Inform. 2021;28(1):e100274. 10.1136/bmjhci-2020-100274 Luschi A, Nesi P, Iadanza E. Evidence-based clinical engineering: Health information technology adverse events identification and classification with natural language processing. Heliyon. 2023;9(11):e21723. 10.1016/j.heliyon.2023.e21723 Mertes PM, Morgand C, Barach P, Jurkolow G, Assmann KE, Dufetelle E, et al. Validation of a natural language processing algorithm using national reporting data to improve identification of anesthesia-related ADVerse evENTs: The "ADVENTURE" study. Anaesth Crit Care Pain Med. 2024;43(4):101390. 10.1016/j.bja.2024.03.015 Fong A. Realizing the Power of Text Mining and Natural Language Processing for Analyzing Patient Safety Event Narratives: The Challenges and Path Forward. J Patient Saf. 2021;17(8):e834-e836. 10.1097/PTS.0000000000000805 Platt JE, Raj M, Wienroth M. An Analysis of the Learning Health System in Its First Decade in Practice: Scoping Review. J Med Internet Res. 2020;22(3):e17026. 10.2196/17026 Chen H, Cohen E, Wilson D, Alfred M. A Machine Learning Approach with Human-AI Collaboration for Automated Classification of Patient Safety Event Reports: Algorithm Development and Validation Study. JMIR Hum Factors. 2024;11:e53378. 10.2196/53378 Fong A, Komolafe T, Adams KT, Cohen A, Howe JL, Ratwani RM. Exploration and Initial Development of Text Classification Models to Identify Health Information Technology Usability-Related Patient Safety Event Reports. Appl Clin Inform. 2019;10(3):521-7. 10.1055/s-0039-1693427 Ball R, Talal AH, Dang O, Muñoz M, Markatou M. Trust but Verify: Lessons Learned for the Application of AI to Case-Based Clinical Decision-Making From Postmarketing Drug Safety Assessment at the US Food and Drug Administration. J Med Internet Res. 2024;26:e50274. 10.2196/50274 Ramar K, Oxentenko AS, Dowdy SC. Transforming Health Care Through Quality and Safety. Mayo Clin Proc. 2025;100(8):1385-401. 10.1016/j.mayocp.2025.02.012 Kang H, et al. A novel schema to enhance data quality of patient safety event reports. Appl Clin Inform. 2017;8(4):1028-43. 10.4338/ACI-2017-03-RA-0042 Ramar K, Oxentenko AS, Dowdy SC. Transforming Health Care Through Quality and Safety. Mayo Clin Proc. 2025;100(8):1385-401. 10.1016/j.mayocp.2025.04.012