Artificial Intelligence-Powered Surgical Consent: Patient Insights

Abstract

Introduction The integration of artificial intelligence (AI) in healthcare has revolutionized patient interactions and service delivery. AI's role extends from supporting clinical diagnostics and enhancing operational efficiencies to potentially improving informed consent processes in surgical settings. This study investigates the application of AI, particularly large language models like OpenAI's ChatGPT, in facilitating surgical consent, focusing on patient understanding, satisfaction, and trust. Methods We employed a mixed-methods approach involving 86 participants, including laypeople and medical staff, who engaged in a simulated AI-driven consent process for a tonsillectomy. Participants interacted with ChatGPT-4, which provided detailed procedure explanations, risks, and benefits. Post-interaction, participants completed a survey assessing their experience through quantitative and qualitative measures. Results Participants had a cautiously optimistic response to AI in the surgical consent process. Notably, 71% felt adequately informed, 86% found the information clear, and 71% felt they could make informed decisions. Overall, 71% were satisfied, 57% felt respected and confident, and 57% would recommend it, indicating areas needing refinement. However, concerns about data privacy and the lack of personal interaction were significant, with only 42% reassured about the security of their data. The standardization of information provided by AI was appreciated for potentially reducing human error, but the absence of empathetic human interaction was noted as a drawback. Discussion While AI shows promise in enhancing the consistency and comprehensiveness of information delivered during the consent process, significant challenges remain. These include addressing data privacy concerns and bridging the gap in personal interaction. The potential for AI to misinform due to system "hallucinations" or inherent biases also needs consideration. Future research should focus on refining AI interactions to support more nuanced and empathetic engagements, ensuring that AI supplements rather than replacing human elements in healthcare. Conclusion The integration of AI into surgical consent processes could standardize and potentially improve the delivery of information but must be balanced with efforts to maintain the critical human elements of care. Collaborative efforts between developers, clinicians, and ethicists are essential to optimize AI use, ensuring it complements the traditional consent process while enhancing patient satisfaction and trust.

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