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Transforming Rheumatology Practice: Applications of Generative Artificial Intelligence
Augusto Garcia-Agundez1, Megan Creasman2, Gabriela Schmajuk3
1Division of Rheumatology, University of California San Francisco, 2540 23rd Street, San Francisco, CA 94110, USA.
Rheumatic Diseases Clinics of North America
|July 6, 2026
Summary
Generative artificial intelligence (GenAI) offers potential benefits in rheumatology, improving documentation and reducing cognitive load. However, careful evaluation is needed due to modest efficiency gains and risks like automation bias.
Area of Science:
- Rheumatology
- Artificial Intelligence
- Clinical Informatics
Background:
- Generative artificial intelligence (GenAI) is increasingly integrated into clinical settings.
- The precise role and impact of GenAI in rheumatology workflows are not yet fully established.
Purpose of the Study:
- To review current and emerging GenAI applications in rheumatology.
- To evaluate GenAI's impact on clinical tasks, efficiency, and potential risks.
Main Methods:
- Task-based framework to analyze GenAI applications.
- Literature review of mature tools (AI scribes) and emerging applications (chart summarization, information extraction).
- Assessment of future opportunities in clinical prediction.
Main Results:
- GenAI tools consistently reduce cognitive burden and improve documentation experience.
- Efficiency gains from GenAI are currently modest.
- Significant risks include automation bias and AI-generated inaccuracies (hallucinations).
Conclusions:
- GenAI has substantial potential to enhance rheumatology practice.
- Careful oversight, validation, and risk mitigation are crucial for successful GenAI implementation.
- Further research is needed to optimize GenAI use in rheumatology.
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