John McCue, C David Butler, Raymond C Love, Shelly Spiro, Roy Guharoy
{"title":"A call to action for adverse drug event (ADE) detection and prevention.","authors":"John McCue, C David Butler, Raymond C Love, Shelly Spiro, Roy Guharoy","doi":"10.3389/fdgth.2025.1507967","DOIUrl":null,"url":null,"abstract":"<p><p>Injury from medication use, known as an adverse drug event (ADE) accounts for millions of emergency department visits globally and thousands of hospitalizations annually within the United States. Efforts to prevent and detect ADEs within healthcare systems are complicated by data quality, lack of data standardization, and actionable clinical decision support systems. United States Pharmacopeia (USP) proposes the use of an ADE value set, a standardized grouping of medical terms, to improve the identification, documentation, and use of ADE information in EHRs. Artificial Intelligence and Machine Learning capabilities would be further strengthened through the standardization of ADE data and information.</p>","PeriodicalId":73078,"journal":{"name":"Frontiers in digital health","volume":"7 ","pages":"1507967"},"PeriodicalIF":3.2000,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11986632/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in digital health","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3389/fdgth.2025.1507967","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Injury from medication use, known as an adverse drug event (ADE) accounts for millions of emergency department visits globally and thousands of hospitalizations annually within the United States. Efforts to prevent and detect ADEs within healthcare systems are complicated by data quality, lack of data standardization, and actionable clinical decision support systems. United States Pharmacopeia (USP) proposes the use of an ADE value set, a standardized grouping of medical terms, to improve the identification, documentation, and use of ADE information in EHRs. Artificial Intelligence and Machine Learning capabilities would be further strengthened through the standardization of ADE data and information.