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Nurse Practitioner Students' Perceptions of an Artificial Intelligence Differential Diagnosis Tool: A Pilot Study
Nilufeur McKay1, Peter Palamara1, Adam McCavery1
1Edith Cowan University, School of Nursing and Midwifery, Perth, Western Australia, Australia.
Aim:
The aim of this study is to assess nurse practitioner students' perceptions and engagement with Isabel's artificial intelligence (AI) based differential diagnosis tool to support their decision-making skills during their theoretical and clinical placement training.
Design:
This pilot study used a cross-sectional design.
Methods:
Twenty-six nurse practitioner students provided feedback on their use of an AI differential diagnosis tool in both academic and clinical contexts. This survey used the Post-Study System Usability Questionnaire to assess the engagement levels and usability of the AI tool. Additional questions were included to evaluate the usage patterns, adequacy in training and confidence in diagnosis.
Results:
There were mixed engagement levels: 44.4% (n = 8/18) used Isabel in two subjects-typically one or both clinical placement units-and 27.8% (n = 5/18) in one subject; students most often used the tool to confirm differential diagnoses. Usability was rated positively with the disease ranking, red flag diagnosis and link to national guideline features demonstrating the highest student usage. While most students found the tool beneficial to use during clinical placement and completing university assignments, some reported challenges due to insufficient training, impacting confidence in clinical application.
Conclusion:
Isabel has potential as a valuable educational tool in Nurse Practitioner programs, but successful implementation depends on adequate training and support. The findings highlight the importance of comprehensive training and support to maximise AI tool utilisation, with direct implications for programme curricula, clinical education strategies and potential improvements in diagnostic reasoning skills for future nurse practitioners.
Implications For The Profession And/Or Patient Care:
This study provides an example of integrating artificial intelligence (AI) guided clinical decision-making training in nurse practitioner (NP) education. The findings can be used by educational institutions to trial similar AI-integrated learning approaches, enhancing diagnostic competence and potentially improving patient care outcomes.
Reporting Method:
The Study adhered to the STROBE checklist for reporting.
Patient Or Public Contribution:
No patient or public contribution was made to this study.
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