継続的専門開発(CPD)認定におけるAIによる監視:AIの活用
1Dr. McMahon: President and CEO, Accreditation Council for Continuing Medical Education, Chicago, IL; and Adjunct Professor of Medicine and Medical Education, Northwestern University Feinberg School of Medicine, Chicago, IL.
The Journal of continuing education in the health professions
|December 22, 2025
まとめ
人工知能(AI)は、効率性とデータ統合を改善することにより、継続的専門開発(CPD)の監視を強化することができる。認定機関による責任あるAIの実装は、信頼できる信頼性の高いCPDシステムの維持に不可欠である。
科学分野:
- 医療専門職教育
- 人工知能
- 規制科学
背景:
- 継続的専門開発(CPD)の監視は、信頼できる偏りのない医療専門職教育を保証するために不可欠である。
- CPD監視における人工知能(AI)の応用は、十分に探求されていない分野である。
研究 の 目的:
- CPDの認定監視におけるAIの潜在的な応用を検討すること。
- AIが規制機能における効率性、一貫性、洞察をどのようにサポートできるかを分析すること。
- AI支援監視における人間の判断とガバナンスの必要性を強調すること。
主な方法:
- 現在の文献と専門的ガイダンスの統合。
- 認定機関の規制機能におけるAI応用の分析。
- CPD監視におけるAIに関連する機会とリスクの検討。
主要な成果:
- AIは再認定資料のスクリーニング、リスクの高い活動の特定、傾向の統合、データのリンク、責任あるAI使用の評価を行うことができる。潜在的な利点には、効率性とデータ統合の向上が含まれる。課題には、精度、公平性、透明性、セキュリティ、公衆の信頼が含まれる。
結論:
- 認定システムは、専門職教育を促進し、CPDの完全性を保護するために、責任あるAIの使用をモデル化することができる。
- 責任あるAIの統合には、アカウンタビリティ、透明性、公平性、セキュリティの原則が必要である。
- AIは、監視の効率性と信頼性を向上させ、グローバルなCPDの信頼性を強化することができる。
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