โก Quick Summary
A recent pilot study explored the use of AI-generated physician avatars for postoperative education, demonstrating a remarkable 99% accuracy in answering patient queries. The findings suggest that these avatars can enhance patient trust and engagement in clinical communication.
๐ Key Details
- ๐ Participants: 30 plastic surgery patients at Mayo Clinic, USA
- ๐งฉ Technology: AI-generated surgeon avatar developed using the HeyGen IV model
- โ๏ธ Interaction: Patients engaged with the avatar through natural voice queries
- ๐ Performance: 99% accuracy in responding to patient queries
๐ Key Takeaways
- ๐ค AI avatars can provide scalable, 24/7 clinical communication for patients.
- ๐ก High usability was indicated by a mean System Usability Scale score of 87.7.
- ๐ Trust levels were exceptionally high, with 100% of participants finding the avatar trustworthy.
- ๐ Eeriness was minimal, with a mean score of 1.57.
- ๐จ Visual appeal was noted by 96.7% of participants who found the avatar pleasing.
- ๐ Familiarity with the physician enhanced trust in the avatar’s information.
- ๐ Prior exposure to deepfakes correlated with higher acceptance ratings.
- ๐ฃ๏ธ Qualitative feedback highlighted the avatar’s clarity and efficiency in communication.
๐ Background
The integration of generative AI and synthetic media has paved the way for the development of realistic Embodied Conversational Agents (ECAs), or avatars. These avatars can replicate human likenesses, including faces and voices, creating what are known as “digital twins” of physicians. This technology holds the potential to revolutionize patient education and communication, particularly in the postoperative context.
๐๏ธ Study
Conducted at the Mayo Clinic between July and August 2025, this pilot feasibility study aimed to evaluate patient perceptions of an AI-generated surgeon avatar designed for postoperative education. The avatar was developed using the HeyGen IV model in Python, allowing patients to interact with it through natural voice queries. The responses covered ten common postoperative topics, and patient perceptions were assessed using validated scales.
๐ Results
The avatar system demonstrated impressive performance, accurately answering 297 out of 300 queries, resulting in a 99% accuracy rate. Usability was rated highly, with a mean score of 87.7, and engagement was also significant, averaging 4.27 on a 5-point scale. Trust emerged as the most positively rated domain, with all participants finding the avatar’s information credible. Notably, the avatar was recognized as their surgeon by 86.6% of participants, although many acknowledged its artificial nature.
๐ Impact and Implications
The findings from this study suggest that AI-generated physician avatars can serve as a valuable tool for enhancing patient education and communication in clinical settings. By providing a scalable solution for postoperative education, these avatars can help maintain trust in clinical relationships while offering patients convenient access to information. The study highlights the importance of transparency regarding the synthetic nature of the technology, which can bolster trust rather than diminish it.
๐ฎ Conclusion
This pilot study underscores the potential of AI-generated physician avatars in transforming patient education and communication. With high levels of acceptance and trust, these avatars could play a crucial role in postoperative care, offering patients reliable information and support. As we continue to explore the integration of AI in healthcare, further research is essential to refine these technologies and maximize their benefits for patient outcomes.
๐ฌ Your comments
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Artificial Intelligence Physician Avatars for Patient Education: A Pilot Study.
Abstract
Background: Generative AI and synthetic media have enabled realistic human Embodied Conversational Agents (ECAs) or avatars. A subset of this technology replicates faces and voices to create realistic likenesses. When combined with avatars, these methods enable the creation of “digital twins” of physicians, offering patients scalable, 24/7 clinical communication outside the immediate clinical environment. This study evaluated surgical patient perceptions of an AI-generated surgeon avatar for postoperative education. Methods: We conducted a pilot feasibility study with 30 plastic surgery patients at Mayo Clinic, USA (July-August 2025). A bespoke interactive surgeon avatar was developed in Python using the HeyGen IV model to reproduce the surgeon’s likeness. Patients interacted with the avatar through natural voice queries, which were mapped to predetermined, pre-recorded video responses covering ten common postoperative topics. Patient perceptions were assessed using validated scales of usability, engagement, trust, eeriness, and realism, supplemented by qualitative feedback. Results: The avatar system reliably answered 297 of 300 patient queries (99%). Usability was excellent (mean System Usability Scale score = 87.7 ยฑ 11.5) and engagement high (mean 4.27 ยฑ 0.23). Trust was the highest-rated domain, with all participants (100%) finding the avatar trustworthy and its information believable. Eeriness was minimal (mean = 1.57 ยฑ 0.48), and 96.7% found the avatar visually pleasing. Most participants (86.6%) recognized the avatar as their surgeon, although many still identified it as artificial; voice resemblance was less convincing (70%). Interestingly, participants with prior exposure to deepfakes demonstrated consistently higher acceptance, rating usability, trust, and engagement 5-10% higher than those without prior exposure. Qualitative feedback highlighted clarity, efficiency, and convenience, while noting limitations in realism and conversational scope. Conclusions: The AI-generated physician avatar achieved high patient acceptance without triggering uncanny valley effects. Transparency about the synthetic nature of the technology enhanced, rather than diminished, trust. Familiarity with the physician and institutional credibility likely played a key role in the high trust scores observed. When implemented transparently and with appropriate safeguards, synthetic physician avatars may offer a scalable solution for postoperative education while preserving trust in clinical relationships.
Author: [‘Haider SA’, ‘Prabha S’, ‘Gomez-Cabello CA’, ‘Genovese A’, ‘Collaco B’, ‘Wood N’, ‘Lifson MA’, ‘Bagaria S’, ‘Tao C’, ‘Forte AJ’]
Journal: J Clin Med
Citation: Haider SA, et al. Artificial Intelligence Physician Avatars for Patient Education: A Pilot Study. Artificial Intelligence Physician Avatars for Patient Education: A Pilot Study. 2025; 14:(unknown pages). doi: 10.3390/jcm14238595