Nurses' perceptions of the design, implementation, and adoption of machine learning clinical decision support: A descriptive qualitative study.
Introduction: The purpose of this study was to explore nurses' perspectives on Machine Learning Clinical Decision Support (ML CDS) design, development, implementation, and adoption. Design: Qualitative descriptive study. Methods: Nurses (n = 17) participated in semi‐structured interviews. Data were...
| Publicado en: | Journal of Nursing Scholarship Vol. 57; no. 1; pp. 82 - 95 |
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| Autores principales: | , , , , , , |
| Formato: | pictorial research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
Jan2025
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=183980038&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 183980038 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15276546 6QP jtl: Journal of Nursing Scholarship issn: 15276546 maglogo: Y pubinfo: dt: Jan2025 vid: 57 iid: 1 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 183980038 177960291 183980038 183980038 10.1111/jnu.13001 183980038 ppf: 82 ppct: 13 formats: tig: atl: Nurses' perceptions of the design, implementation, and adoption of machine learning clinical decision support: A descriptive qualitative study. aug: au: Wieben, Ann M. Alreshidi, Bader G. Douthit, Brian J. Sileo, Marisa Vyas, Pankaj Steege, Linsey Gilmore‐Bykovskyi, Andrea affil: University of Wisconsin‐Madison School of Nursing, Madison Wisconsin,, USA sug: subj: Nurse Attitudes Machine Learning Methods Decision Support Systems, Clinical Utilization Artificial Intelligence Nursing Staff, Hospital Psychosocial Factors Database Design Implementation Science Adaptation, Physiological Human Funding Source Female Adult Middle Age Qualitative Studies Descriptive Research Semi-Structured Interview Thematic Analysis Questionnaires Health Personnel Psychosocial Factors Attitude of Health Personnel Usability Study Nursing Informatics Change Management Clinical Reasoning Technology, Medical Decision Making, Computer Assisted Methods Professional Autonomy Descriptive Statistics Comparative Studies Adult: 19-44 years Middle Aged: 45-64 years Female ab: Introduction: The purpose of this study was to explore nurses' perspectives on Machine Learning Clinical Decision Support (ML CDS) design, development, implementation, and adoption. Design: Qualitative descriptive study. Methods: Nurses (n = 17) participated in semi‐structured interviews. Data were transcribed, coded, and analyzed using Thematic analysis methods as described by Braun and Clarke. Results: Four major themes and 14 sub‐themes highlight nurses' perspectives on autonomy in decision‐making, the influence of prior experience in shaping their preferences for use of novel CDS tools, the need for clarity in why ML CDS is useful in improving practice/outcomes, and their desire to have nursing integrated in design and implementation of these tools. Conclusion: This study provided insights into nurse perceptions regarding the utility and usability of ML CDS as well as the influence of previous experiences with technology and CDS, change management strategies needed at the time of implementation of ML CDS, the importance of nurse‐perceived engagement in the development process, nurse information needs at the time of ML CDS deployment, and the perceived impact of ML CDS on nurse decision making autonomy. Clinical Relevance: This study contributes to the body of knowledge about the use of AI and machine learning (ML) in nursing practice. Through generation of insights drawn from nurses' perspectives, these findings can inform successful design and adoption of ML Clinical Decision Support. pubtype: Academic Journal doctype: pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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