Anna van der Gaag MSc, PhD, Robert Jago BA, MPhil (Cantab), Ann Gallagher SRN, MRN, BA, MA, PhD, Kostas Stathis PhD, Michelle Webster BA, MSc, PhD, Zubin Austin BScPhm, MBA, MISc, PhD, FCAHS
{"title":"Artificial Intelligence in Health Professions Regulation: An Exploratory Qualitative Study of Nurse Regulators in Three Jurisdictions","authors":"Anna van der Gaag MSc, PhD, Robert Jago BA, MPhil (Cantab), Ann Gallagher SRN, MRN, BA, MA, PhD, Kostas Stathis PhD, Michelle Webster BA, MSc, PhD, Zubin Austin BScPhm, MBA, MISc, PhD, FCAHS","doi":"10.1016/S2155-8256(23)00087-X","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><p>Artificial intelligence (AI) refers to a broad group of technologies that are increasingly commonplace in everyday life; however, they have had only limited application in regulatory practice.</p></div><div><h3>Purpose</h3><p>The present study explored nursing regulators’ perceptions of the role and value of AI in regulation and potential barriers and facilitators to the uptake and implementation of AI.</p></div><div><h3>Methods</h3><p>Three facilitated focus group sessions with 28 representatives of regulators from Australia, the United Kingdom, and the United States were conducted. Content analysis of verbatim transcripts was completed.</p></div><div><h3>Results</h3><p>Key themes that emerged included (a) interest in how AI could enhance sustainability and improve cost-effectiveness of certain regulatory processes and (b) concerns regarding how the term “artificial intelligence” itself could be problematic. Specific barriers to the uptake of AI in regulation included concerns regarding codification of system bias, negative public perception, and lack of clarity around accountability for decision-making. Facilitators to implementation included enhancing the consistency of processes and improving the decision-making and utility in supporting trend analyses and audit functions.</p></div><div><h3>Conclusion</h3><p>Additional work in exploring how best to incorporate evolving AI technologies in regulatory practice—and what they should be named—is required, but these findings suggest that promising outcomes may lie ahead.</p></div>","PeriodicalId":46153,"journal":{"name":"Journal of Nursing Regulation","volume":"14 2","pages":"Pages 10-17"},"PeriodicalIF":4.2000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Nursing Regulation","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S215582562300087X","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Artificial intelligence (AI) refers to a broad group of technologies that are increasingly commonplace in everyday life; however, they have had only limited application in regulatory practice.
Purpose
The present study explored nursing regulators’ perceptions of the role and value of AI in regulation and potential barriers and facilitators to the uptake and implementation of AI.
Methods
Three facilitated focus group sessions with 28 representatives of regulators from Australia, the United Kingdom, and the United States were conducted. Content analysis of verbatim transcripts was completed.
Results
Key themes that emerged included (a) interest in how AI could enhance sustainability and improve cost-effectiveness of certain regulatory processes and (b) concerns regarding how the term “artificial intelligence” itself could be problematic. Specific barriers to the uptake of AI in regulation included concerns regarding codification of system bias, negative public perception, and lack of clarity around accountability for decision-making. Facilitators to implementation included enhancing the consistency of processes and improving the decision-making and utility in supporting trend analyses and audit functions.
Conclusion
Additional work in exploring how best to incorporate evolving AI technologies in regulatory practice—and what they should be named—is required, but these findings suggest that promising outcomes may lie ahead.
期刊介绍:
Journal of Nursing Regulation (JNR), the official journal of the National Council of State Boards of Nursing (NCSBN®), is a quarterly, peer-reviewed, academic and professional journal. It publishes scholarly articles that advance the science of nursing regulation, promote the mission and vision of NCSBN, and enhance communication and collaboration among nurse regulators, educators, practitioners, and the scientific community. The journal supports evidence-based regulation, addresses issues related to patient safety, and highlights current nursing regulatory issues, programs, and projects in both the United States and the international community. In publishing JNR, NCSBN''s goal is to develop and share knowledge related to nursing and other healthcare regulation across continents and to promote a greater awareness of regulatory issues among all nurses.