AI Scribes in Mental Health Care: Balancing Efficiency, Safety and Therapeutic Presence
Tracks
Monarch
| Thursday, November 5, 2026 |
| 11:50 AM - 12:20 PM |
Overview
Alireza Ahmadvand, Griffith University
Three Key Learnings
1. AI scribes can influence clinical understanding in mental health care
Variations in accuracy and completeness may affect how patient narratives are captured, particularly in complex or high-risk presentations (e.g. self-harm, psychosis), with implications for care and safety.
2. Clinical judgement and therapeutic context remain central
AI-generated notes require active review and interpretation. Clinicians must ensure documentation reflects the patient’s experience and supports safe, person-centred care.
3. Thoughtful, context-aware integration is essential
Adoption should be guided by critical appraisal, awareness of limitations, and alignment with ethical, clinical and medico-legal responsibilities, particularly in resource-limited and high-risk settings.
Presenter
A/prof. Alireza Ahmadvand
Associate Professor In Primary Care
Griffith University
AI Scribes in Mental Health Care: Balancing Efficiency, Safety and Therapeutic Presence
Presentation Overview
Background/Aim:
This workshop explores the role of AI scribes in mental health care through a human-centred and clinically grounded lens. It examines how these tools may influence documentation, clinician workload, attention, and the therapeutic relationship. Drawing on emerging evidence from comparative evaluations in psychiatric scenarios, the workshop will highlight both the potential benefits (e.g. reduced cognitive load) and risks (e.g. loss of nuance, misrepresentation of patient narratives). Participants will develop practical approaches to using AI scribes in ways that support safe, person-centred care while maintaining professional/ethical standards.
Method:
This interactive workshop integrates short presentations, real-world examples, small-group discussion and applied exercises. Participants will engage with AI-generated notes from mental health consultations and explore how differences in documentation may affect clinical understanding, decision-making and therapeutic engagement. Case-based scenarios (e.g. depression, psychosis, self-harm) will prompt discussion on interpretation, risk, and communication. Facilitated activities will focus on identifying when AI supports care and when it may compromise it, with participants applying practical strategies to review, adapt and safely incorporate AI-generated documentation into their clinical workflows.
Conclusion:
AI scribes offer opportunities to reduce administrative burden in mental health care, but their integration must be approached with careful attention to safety, clinical judgement and therapeutic presence. This workshop positions AI scribes within the broader context of person-centred care, highlighting the need to balance efficiency with the preservation of meaningful clinician–patient interactions. Participants will leave with practical strategies to use these tools thoughtfully, ensuring that technology enhances rather than diminishes the quality, safety and relational aspects of mental health care.
Relevance to Rural Mental Health:
AI scribes may reduce workload and support workforce sustainability in rural mental health settings. However, risks around accuracy and loss of nuance require oversight. This workshop supports safe, person-centred adoption to ensure technology enhances care and therapeutic relationships in resource-limited environments.
This workshop explores the role of AI scribes in mental health care through a human-centred and clinically grounded lens. It examines how these tools may influence documentation, clinician workload, attention, and the therapeutic relationship. Drawing on emerging evidence from comparative evaluations in psychiatric scenarios, the workshop will highlight both the potential benefits (e.g. reduced cognitive load) and risks (e.g. loss of nuance, misrepresentation of patient narratives). Participants will develop practical approaches to using AI scribes in ways that support safe, person-centred care while maintaining professional/ethical standards.
Method:
This interactive workshop integrates short presentations, real-world examples, small-group discussion and applied exercises. Participants will engage with AI-generated notes from mental health consultations and explore how differences in documentation may affect clinical understanding, decision-making and therapeutic engagement. Case-based scenarios (e.g. depression, psychosis, self-harm) will prompt discussion on interpretation, risk, and communication. Facilitated activities will focus on identifying when AI supports care and when it may compromise it, with participants applying practical strategies to review, adapt and safely incorporate AI-generated documentation into their clinical workflows.
Conclusion:
AI scribes offer opportunities to reduce administrative burden in mental health care, but their integration must be approached with careful attention to safety, clinical judgement and therapeutic presence. This workshop positions AI scribes within the broader context of person-centred care, highlighting the need to balance efficiency with the preservation of meaningful clinician–patient interactions. Participants will leave with practical strategies to use these tools thoughtfully, ensuring that technology enhances rather than diminishes the quality, safety and relational aspects of mental health care.
Relevance to Rural Mental Health:
AI scribes may reduce workload and support workforce sustainability in rural mental health settings. However, risks around accuracy and loss of nuance require oversight. This workshop supports safe, person-centred adoption to ensure technology enhances care and therapeutic relationships in resource-limited environments.
Biography
Dr Alireza Ahmadvand is a General Practitioner and digital health academic in Brisbane, Australia, and Associate Professor in Primary Care at Griffith University. His work focuses on integrating artificial intelligence and digital technologies into primary care to improve clinical decision-making, education and patient outcomes. He has led research on digital health diagnostics, AI tools in gastroenterology, and generative AI in general practice. He collaborates across disciplines to advance innovation in healthcare delivery and digital literacy. With over 60 peer-reviewed publications, his academic and clinical work aims to translate emerging technologies into practical benefits for patients, clinicians and health systems.
