Navigating the potential and pitfalls of large language models in patient-centered medication guidance and self-decision support
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View abstract on PubMed
Summary
This summary is machine-generated.Large Language Models (LLMs) offer accessible medication information for patients but pose risks of misinformation. These AI tools should supplement, not replace, professional healthcare guidance for safe medication management.
Area Of Science
- Medical Informatics
- Artificial Intelligence in Healthcare
- Patient Education
Background
- Large Language Models (LLMs) are increasingly used in patient education.
- This perspective builds on a scoping review of LLMs in patient education.
- Focus is on the specific role of LLMs in medication guidance.
Purpose Of The Study
- Examine the role of LLMs in medication guidance.
- Analyze current capabilities and limitations of LLMs in this domain.
- Raise questions about the integration of LLMs into medication management.
Main Methods
- Perspective piece analyzing existing literature and AI capabilities.
- Discussion of potential benefits and risks.
- Identification of challenges and areas for future consideration.
Main Results
- LLMs can generate comprehensive drug information, potentially enhancing patient autonomy.
- Significant risks include misinformation and lack of access to individual patient data.
- Safety concerns arise when patients rely solely on AI for self-medication decisions.
Conclusions
- LLMs show potential in medication guidance but have critical limitations.
- Regulatory oversight is crucial to ensure LLMs supplement professional healthcare.
- Emphasis on using LLMs as aids, not replacements, for healthcare advice.
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