⚡ Quick Summary
A recent nationwide survey of U.S. rheumatology fellows reveals that 67.9% support the integration of artificial intelligence (AI) education into their fellowship programs. While fellows recognize AI’s potential to enhance efficiency, they also express concerns regarding charting errors and over-reliance on technology.
🔍 Key Details
- 📊 Participants: 95 U.S. rheumatology fellows
- 🗓️ Survey Period: October to December 2023
- 📈 Response Rate: 85-95% per question
- ⚖️ Gender Distribution: 57.6% female
- 🔍 Age Range: 66.3% aged 30-35
- 🎓 Fellowship Year: 60.2% in their first year
🔑 Key Takeaways
- 🤖 AI Familiarity: Positive correlation with confidence (Spearman’s rho = 0.216, p = 0.044).
- 📚 Education Support: 67.9% favor AI education in fellowship programs.
- 🕒 Efficiency Gains: 86.05% believe AI can reduce charting time.
- 🔄 Task Automation: 73.26% see potential in automating routine tasks.
- ⚠️ Concerns: 67.86% worry about charting errors; 61.90% about over-reliance on AI.
- 🙅♂️ Job Security: 84.52% disagree that AI will replace rheumatologists.
- 🌟 Enthusiasm: Fellows show eagerness for AI integration despite reservations.
📚 Background
The integration of artificial intelligence into healthcare is rapidly evolving, promising to enhance clinical practices, diagnostics, and patient care. However, the successful implementation of AI technologies in fields like rheumatology requires a thorough understanding of the perspectives and concerns of healthcare professionals, particularly those in training.
🗒️ Study
This study utilized a cross-sectional survey conducted via Qualtrics, targeting U.S. rheumatology fellows. The survey included a mix of multiple-choice, Likert scale, and open-ended questions to gather insights on demographics, AI awareness, usage, and perceptions. The research adhered to ethical guidelines and received IRB approval, aiming to reach a total of 528 fellows.
📈 Results
The findings indicate a significant interest in AI among rheumatology fellows, with a majority recognizing its potential benefits in reducing administrative burdens. However, concerns about the accuracy of AI-generated data and the risk of over-dependence were prevalent. The statistical analysis revealed a noteworthy correlation between familiarity with AI and confidence in its application.
🌍 Impact and Implications
The insights from this survey highlight the need for educational programs that incorporate AI training for rheumatology fellows. By addressing the concerns raised and fostering a collaborative environment, the integration of AI can be achieved responsibly, prioritizing patient safety and ethical standards. This could lead to improved patient outcomes and more efficient healthcare delivery.
🔮 Conclusion
The enthusiasm for AI among U.S. rheumatology fellows is evident, yet it is accompanied by valid concerns regarding its implementation. As the field of rheumatology continues to evolve, it is crucial to balance the benefits of AI with the ethical considerations and potential risks. Continued dialogue and education will be essential in shaping the future of AI in healthcare.
💬 Your comments
What are your thoughts on the integration of AI in rheumatology? Do you believe it will enhance patient care or pose more challenges? 💬 Share your insights in the comments below or connect with us on social media:
Artificial intelligence in rheumatology: perspectives and insights from a nationwide survey of U.S. rheumatology fellows.
Abstract
Artificial Intelligence (AI) is poised to revolutionize healthcare by enhancing clinical practice, diagnostics, and patient care. Although AI offers potential benefits through data-driven insights and personalized treatments, challenges related to implementation, barriers, and ethical considerations necessitate further investigation. We conducted a cross-sectional survey using Qualtrics from October to December 2023 to evaluate U.S. rheumatology fellows’ perspectives on AI in healthcare. The survey was disseminated via email to program directors, who forwarded it to their fellows. It included multiple-choice, Likert scale, and open-ended questions covering demographics, AI awareness, usage, and perceptions. Statistical analyses were performed using Spearman correlation and Chi-Square tests. The study received IRB approval and adhered to STROBE guidelines. The survey aimed to reach 528 U.S. rheumatology fellows. 95 fellows accessed the survey with response rate to each question varying between 85 and 95 participants. 57.6% were females, 66.3% aged 30-35, and 60.2% in their first fellowship year. There was a positive correlation between AI familiarity and confidence (Spearman’s rho = 0.216, p = 0.044). Furthermore, 67.9% supported incorporating AI education into fellowship programs, with a significant relationship (p < 0.005) between AI confidence and support for AI education. Fellows recognized AI's benefits in reducing chart time (86.05%) and automating tasks (73.26%), but expressed concerns about charting errors (67.86%) and over-reliance (61.90%). Most (84.52%) disagreed with the notion of AI replacing them. Rheumatology fellows exhibit enthusiasm for AI integration yet have reservations about its implementation and ethical implications. Addressing these challenges through collaborative efforts can ensure responsible AI integration, prioritizing patient safety and ethical standards in rheumatology and beyond.
Author: [‘Purohit R’, ‘Saineni S’, ‘Chalise S’, ‘Mathai R’, ‘Sambandam R’, ‘Medina-Perez R’, ‘Bhanusali N’]
Journal: Rheumatol Int
Citation: Purohit R, et al. Artificial intelligence in rheumatology: perspectives and insights from a nationwide survey of U.S. rheumatology fellows. Artificial intelligence in rheumatology: perspectives and insights from a nationwide survey of U.S. rheumatology fellows. 2024; (unknown volume):(unknown pages). doi: 10.1007/s00296-024-05737-8