Vollständiger Abstract
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Abstract Objectives Human Factors (HF) principles are essential for safe and effective clinical decision support (CDS), yet existing guidance is fragmented and rarely evaluated in real world settings. A novel, evidence-based, vendor-agnostic HF-informed guideline was developed to address this gap. This study evaluated its perceived usefulness, usability, and impact on CDS design and optimization. Materials and Methods A 2-phase explanatory sequential mixed methods approach was used. Phase 1 involved a survey of guideline users (n = 25) assessing usefulness, ease of use, satisfaction, and influence on decision-making. Phase 2 included semi-structured interviews (n = 10) to explore real-world application experiences. Quantitative data were analyzed descriptively, and qualitative data were analyzed thematically using a general inductive approach. Results Findings were consistently positive. Participants reported that the guideline was easy to use and supported structured, evidence-based CDS decision-making. It improved confidence in selecting and designing CDS interventions, with particular value placed on its consolidated format and step-by-step approach. Suggested enhancements included adding practical tools, worked examples, and case studies to support broader application across contexts. Discussion This study represents the first real-world evaluation of a consolidated HF-informed CDS guideline, addressing the gap between theory and practice. Results indicate that integrated, accessible HF guidance can strengthen consistency and quality in CDS design, particularly when embedded within routine workflows and governance processes. Conclusion The guideline is a valuable, practical resource for CDS design and optimization. Future research should assess its impact on post-implementation optimization and include objective measures of usability, safety, and CDS effectiveness to further demonstrate its value.
Bibliografischer Nachweis
Publikationsdaten
- Autor:innen
- Selvana Awad, Thomas Loveday, Andrew Baillie, Melissa T Baysari
- Quelle
- Journal of the American Medical Informatics Association
- Publikation
- 2026-01-01
- Band / Ausgabe
- Nicht angegeben
- Seiten
- Nicht angegeben
- ISSN / ISBN
- 1067-5027, 1527-974X
- Zitationen
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Zitierfähiger Nachweis
Selvana Awad, Thomas Loveday, Andrew Baillie, Melissa T Baysari (2026). Evaluation of a clinical decision support design guideline. Journal of the American Medical Informatics Association. https://doi.org/10.1093/jamia/ocag138
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Themen, Förderung und Nutzung
Lizenzhinweise: Lizenz 1