
Exploring the role of AI chatbots in patient education, this analysis delves into recent studies presented at the 2024 AAOS Annual Meeting. Despite limitations in accuracy, chatbots powered by large language models show promise in assisting clinicians and tailoring patient education strategies. Through comparative studies and real-world applications, insights are gleaned into the evolving landscape of healthcare communication and the potential for AI chatbots to bridge gaps in information dissemination.
AI chatbots, driven by large language models, have emerged as transformative tools in healthcare communication. Recent studies presented at the 2024 AAOS Annual Meeting have scrutinized their efficacy in patient education. While acknowledging limitations, these investigations highlight the potential of AI chatbots to complement clinician expertise and personalize educational content. By examining comparative performance and real-world applications, this analysis seeks to elucidate the evolving role of AI chatbots in addressing informational needs within healthcare settings.
Presented at the 2024 Annual Meeting of the American Academy of Orthopaedic Surgeons (AAOS), three studies shed light on the efficacy of AI chatbots, underscoring both their limitations and opportunities for enhancing patient care.
Large language models, such as Open AI ChatGPT, Google Bard, and BingAI, have revolutionized healthcare by offering patients accessible avenues to acquire medical knowledge. However, while these chatbots can provide basic information, the studies reveal that orthopaedists remain the primary source for comprehensive and accurate medical guidance.
In a comparative study, three prominent chatbots were tasked with answering orthopaedic-related queries, revealing discrepancies in their performance. ChatGPT demonstrated the highest success rate, accurately addressing critical aspects of inquiries in 76.7% of cases. Nevertheless, all chatbots exhibited limitations, often failing to gather patient history and deviating from established standards of care.
Similarly, a study focusing on knee and hip replacement inquiries found that while ChatGPT could provide partially accurate responses, orthopaedic surgeons still outperformed in delivering comprehensive information. Despite these limitations, ChatGPT showcased potential in identifying common patient questions, highlighting its role in guiding clinician-led patient education.
Moreover, in a separate investigation, ChatGPT displayed proficiency in retrieving relevant information about the Latarjet procedure, outperforming Google search results. By generating a comprehensive list of frequently asked questions (FAQs), ChatGPT showcased its ability to offer nuanced insights into potential risks, recovery timelines, and surgical evaluations.
These findings underscore the evolving landscape of AI in healthcare, emphasizing the need for critical evaluation and integration into existing medical practices. While AI chatbots present opportunities for augmenting patient education, concerns regarding medical misinformation and patient trust remain pertinent.
Currently, patient trust in AI chatbots and generative AI is moderate, with apprehensions regarding the accuracy and validity of the information provided. However, as patients become more familiar with AI in healthcare, there is a potential shift towards greater acceptance and utilization of these tools.
AI chatbots represent a promising avenue for enhancing patient education in healthcare. Despite challenges in accuracy, recent studies underscore their potential to support clinicians and tailor educational content to individual patient needs. As the field continues to evolve, addressing concerns regarding accuracy and trust will be crucial in harnessing the full potential of AI chatbots. Moving forward, integrating these tools into existing healthcare practices can facilitate more effective communication and ultimately improve patient outcomes.