護理教育的未來－－學習人工智慧之必要元素與實施策略

The Future of Nursing Education: Necessary Elements and Implementation Strategies for Learning Artificial Intelligence

隨著人口老化平均餘命的延長，多重共病與照護複雜度，不僅增加醫療負載，更對照護體系帶來沉重的負擔；資源不足所面臨嚴重挑戰是亟待克服的難題。人工智慧（artificial intelligence, AI）包括調查、整合、學習、預測和決策等功能，透過AI在臨床照護中的應用，不僅改善工作流程提高效率，也提升照護品質與降低人力需求。雖然AI的應用在健康照護實務中日益蓬勃，智慧健康科技導入更是醫療健康衛生政策的趨勢，但醫護教育領域對於AI的運用與訓練相對不足。當前護理教育必須積極面對AI世代的來臨，培養具備理解與應用AI能力的護理師，將AI知能的培訓整合入醫護課程和臨床實習，讓第一線護理人員能善用AI技術，創造高品質、高效能且安全的照護。因此，本文彙整文獻常見的人工智慧模式、護理人工智慧教育所應培訓之六大核心能力，以及相對應學習與實踐之面向，提供護理教育與實務在職培訓之參考。期能在醫療照護困境之際，護理人員能成為創新改革照護體系的尖兵，成為引領照護轉型的先驅。

As populations age, average life expectancy increases and the complexity of diseases rises, leading to nursing care and healthcare systems facing severe challenges related to inadequate resources. Artificial intelligence (AI), including elements such as investigation, integration, learning, prediction, and decision-making, holds significant potential for application in clinical care not only to enhance care quality but also to help guide the future direction of healthcare. AI applications are already being increasingly utilized to improve the quality of clinical care and to streamline workflows. However, because nursing education has lagged behind in terms of adopting AI, greater attention must be given to training up nursing students with AI-related knowledge and application skills. AI technologies should be integrated into nursing curricula and clinical internships to adapt to the rapidly changing high-tech healthcare environment, enabling the more-effective use of AI technology in providing high-quality and safe nursing care.