Use of Simulation to Study Nurses’ Acceptance and Nonacceptance of Clinical Decision Support Suggestions
Open accessAbstract
Our long-term goal was to ensure nurse clinical decision support works as intended before full deployment in clinical practice. As part of a broader effort, this pilot project explored factors influencing acceptance/nonacceptance of eight clinical decision support suggestions displayed in an electronic health record-based nursing plan of care software prototype. A diverse sample of 21 nurses participated in this high-fidelity clinical simulation experience and completed a questionnaire to assess reasons for accepting/not accepting the clinical decision support suggestions. Of 168 total suggestions displayed during the experiment (eight for each of the 21 nurses), 123 (73.2%) were accepted, and 45 (26.8%) were not accepted. The mode number of acceptances by nurses was seven of eight, with only two of 21 nurses accepting all. The main reason for clinical decision support acceptance was the nurse's belief that the suggestions were good for the patient (100%), with other features providing secondary reinforcement. Reasons for nonacceptance were less clear, with fewer than half of the subjects indicating low confidence in the evidence. This study provides preliminary evidence that high-quality simulation and targeted questionnaires about specific clinical decision support selections offer a cost-effective means for testing before full deployment in clinical practice.
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Medical experience is a significant factor influencing self-reported trust and reliance behavior.
“Our research identified medical experience as a significant factor influencing self-reported trust and reliance behavior, which is consistent with previous research [ 58 - 60 ].”
From Psychological Factors Influencing Appropriate Reliance on AI-enabled Clinical Decision Support Systems: Experimental Web-Based Study Among Dermatologists (2025) · cites this paper as [60]
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“Our research identified medical experience as a significant factor influencing self-reported trust and reliance behavior, which is consistent with previous research [58-60].”
- Authors
- SOUSA, V. E. C., LOPEZ, K. D., FEBRETTI, A., STIFTER, J., YAO, Y., JOHNSON, A., WILKIE, D. J., & KEENAN, G. M.
- Affiliations
- University of Florida (US)
- Venue
- CIN: Computers, Informatics, Nursing
- Published
- 2015-10
- Volume
- 33
- Issue
- 10
- Pages
- 465-472
- ISSN
- 1538-2931 (ISSN-L)
- PMC
- PMC4607642
- OpenAlex
- W2410174273
- Cited by
- 18
- References
- 20
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 2 · 2022: 2 · 2021: 1 · 2020: 1 · 2019: 1 · 2018: 2 · 2017: 4 · 2016: 1
- FWCI
- 4.50
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- CIN Computers Informatics Nursing (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- University of Illinois at Chicago
- National Institute of Nursing Research (R01NR012949)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Diagnosis and Documentation
- Keywords
- clinical decision support, electronic health records, high-fidelity clinical simulation, simulation-based testing, nursing decision-making
- MeSH terms
- Simulation Training, Adult, Aged, Attitude of Health Personnel, Attitude to Computers, Clinical Competence, Female, Humans, Male, Middle Aged, Nursing Staff, Hospital, Pilot Projects, Surveys and Questionnaires, Nursing Methodology Research, Decision Support Systems, Clinical, Nursing Informatics, Electronic Health Records
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