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Generative AI in clinical practice: how should rheumatologists evaluate and monitor emerging tools?

Generative artificial intelligence (AI) is increasingly being used in rheumatology practice, to assist with tasks such as documentation, record summarization, and clinical decision support. Rheumatologists need a practical approach to determining what evidence and oversight each application requires. This narrative review proposes a framework based on two dimensions: contextual complexity and influence on patient care. Greater contextual complexity can make errors harder to detect, whereas greater influence on c…

By the Truvace desk1 min read1 sourcePeer-reviewedTRV-2026-2094· cite & verify
Generative AI in clinical practice: how should rheumatologists evaluate and monitor emerging tools?
"MIHANOVICEVA 3 - rheumatology and physiotherapy" by Miroslav Vajdić is licensed under CC BY-SA 2.0. To view a copy of this license, visit https://creativecommons.org/licenses/by-sa/2.0/.

In brief

A narrative review in Arthritis Care & Research proposes a way for rheumatologists to judge generative AI tools used for documentation, record summarization, and clinical decision support. It sorts applications along two dimensions: how complex the context is and how strongly the tool influences patient care.

The framework matters because it matches the level of evidence and monitoring to the potential harm of an undetected error. The authors say existing evidence on benefits, accuracy, and reliability is mixed, and they flag patient outcomes and workable oversight in routine care as priorities for future research.

Main points

  1. The framework rests on contextual complexity, which makes errors harder to detect, and influence on patient care, which raises the consequences of undetected errors.
  2. Low-influence tools are initially evaluated on workflow, usability, and documentation quality.
  3. Tools that synthesize longitudinal information need checks of completeness and source traceability.
  4. Tools influencing diagnosis or treatment require prospective evaluation of clinical benefit and safety.

The gain

Studies of ambient AI scribes suggest they reduce documentation burden for clinicians in rheumatology practice.

The rundown

The review covers uses such as documentation, record summarization, and clinical decision support. It examines evidence for workflow benefits and clinical effectiveness, and considers safety, equity, privacy, governance, and implementation.

On oversight, the authors say vendor evidence should be assessed alongside proportionate local testing and ongoing monitoring. Safeguards should look at performance across patient groups, and changes in a tool's functionality or clinical use should prompt reassessment.

Sources

  1. Peer-reviewedArthritis Care & Research2026-10-20

The debate