Registered Nurses' Experiences of Clinical Decision‐Making: A Qualitative Descriptive Study to Inform Artificial Intelligence‐Assisted Decision Support in Nursing

ABSTRACT Aim To describe registered nurses' experiences of clinical decision‐making and identify needs that may inform future development of artificial‐intelligence‐assisted clinical decision support systems in nursing. Design A qualitative descriptive study. Methods Data were collected between 2022 and 2025 through 16 semi‐structured interviews with registered nurses working in inpatient wards at a Finnish university hospital. The data were analysed using inductive content analysis. Results Perceived challenges in clinical decision‐making were related to organisational issues, multiprofessional collaboration, nurse–patient interactions, professional factors and availability and trustworthiness of data. The findings also identified support needs related to health information management, clinical workflows and quality of nursing care that may inform future artificial intelligence‐assisted clinical decision support system development. Conclusion Nurses experienced multifaceted challenges and needs in clinical decision‐making, shaped by organisational, professional, relational and information‐related factors. Adoption of artificial intelligence‐assisted decision support systems may represent one potential approach to optimising clinical decision‐making, improving patient care quality and enhancing workflow efficiency. Realising these opportunities requires coordinated efforts at individual, organisational and societal levels, including competence development, workflow redesign, strong data governance and a culture that fosters trust in technology. Implications for the Profession and/or Patient Care The findings may inform the future development of artificial intelligence‐assisted clinical decision support systems in nursing. Reporting Method The Consolidated Criteria for Reporting Qualitative Research checklist was used when reporting the results. Patient or Public Contribution Registered nurses participated in the study. Impact What problem did the study address? This paper addresses existing gaps and unmet needs in nursing clinical decision‐making What were the main findings? The main findings highlight several key opportunities for artificial intelligence‐assisted clinical decision support systems in nursing. Where and on whom will the research have an impact? The research may inform efforts to optimise health information management, streamline clinical workflows and improve the quality of nursing care.

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Publication Details

Journal
Journal of Clinical Nursing
Published
2026-10-18
DOI
https://doi.org/10.1111/jocn.70595
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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article

Registered Nurses' Experiences of Clinical Decision‐Making: A Qualitative Descriptive Study to Inform Artificial Intelligence‐Assisted Decision Support in Nursing

Henna Härkönen, Mika Alastalo, Miia Marika Jansson, Petra Suonnansalo et al.
Journal of Clinical Nursing
Artificial Intelligence in Healthcare and Education
article

Registered Nurses' Experiences of Clinical Decision‐Making: A Qualitative Descriptive Study to Inform Artificial Intelligence‐Assisted Decision Support in Nursing

Henna Härkönen, Mika Alastalo, Miia Marika Jansson, Petra Suonnansalo, Wentao Zhou
article en

Abstract

ABSTRACT Aim To describe registered nurses' experiences of clinical decision‐making and identify needs that may inform future development of artificial‐intelligence‐assisted clinical decision support systems in nursing. Design A qualitative descriptive study. Methods Data were collected between 2022 and 2025 through 16 semi‐structured interviews with registered nurses working in inpatient wards at a Finnish university hospital. The data were analysed using inductive content analysis. Results Perceived challenges in clinical decision‐making were related to organisational issues, multiprofessional collaboration, nurse–patient interactions, professional factors and availability and trustworthiness of data. The findings also identified support needs related to health information management, clinical workflows and quality of nursing care that may inform future artificial intelligence‐assisted clinical decision support system development. Conclusion Nurses experienced multifaceted challenges and needs in clinical decision‐making, shaped by organisational, professional, relational and information‐related factors. Adoption of artificial intelligence‐assisted decision support systems may represent one potential approach to optimising clinical decision‐making, improving patient care quality and enhancing workflow efficiency. Realising these opportunities requires coordinated efforts at individual, organisational and societal levels, including competence development, workflow redesign, strong data governance and a culture that fosters trust in technology. Implications for the Profession and/or Patient Care The findings may inform the future development of artificial intelligence‐assisted clinical decision support systems in nursing. Reporting Method The Consolidated Criteria for Reporting Qualitative Research checklist was used when reporting the results. Patient or Public Contribution Registered nurses participated in the study. Impact What problem did the study address? This paper addresses existing gaps and unmet needs in nursing clinical decision‐making What were the main findings? The main findings highlight several key opportunities for artificial intelligence‐assisted clinical decision support systems in nursing. Where and on whom will the research have an impact? The research may inform efforts to optimise health information management, streamline clinical workflows and improve the quality of nursing care.

Journal of Clinical Nursing
RMIT Europe (ES), Laurea University of Applied Sciences (FI), Singapore Management University (SG), University of Oulu (FI)
Openalex Percentile: Top 20%
Artificial Intelligence in Healthcare and Education
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