人工智慧導入實證照護實務之永續發展與挑戰

Sustainable Development and the Challenges of Integrating AI Into Evidence-Based Practice

實證照護實務（evidence-based practice, EBP）意在將實證知識有系統性地轉譯至臨床照護應用，並持續地更新，以提升決策品質與保障病人安全，並展現護理專業之照護品質。當今，隨著人工智慧（artificial intelligence, AI）技術的發展迅速及應用擴大，其導入EBP也正值進行中，例如，協助臨床護理人員提升工作效率與決策品質。然而，AI導入的同時，也帶來照護與倫理議題的挑戰。有鑑於此，本文旨在探討AI導入EBP的多元照護應用，並關注倫理與制度的永續未來以及所面臨挑戰。本文發現AI應用確實有助於提升照護效率與品質，但伴隨而來的資料偏誤、演算法偏差、資料隱私、智慧財產權、技術可及性、倫理當責等風險尚需謹慎處理。尤其當模型設計缺乏透明性或AI監督機制不完善時，易加劇健康不平等與資源失衡的問題。因此，AI能否發揮最大效益，關鍵仍在人為核實與專業責任的落實。未來，AI在EBP中的永續發展需建構具備應用穩健性、演算持續更新、監控機制與倫理治理的架構，以期實現科技下的照護品質提升與病人安全之核心價值。最終，AI科技與照護理念的協同發展，促進智慧醫療照護更具韌性與價值導向的卓越且永續EBP。

Under the framework of evidence-based practice (EBP), evidence-based knowledge is integrated systematically into clinical care and continuously updated to enhance decision-making, ensure patient safety, and showcase nursing excellence. The rapid evolution and popularization of artificial intelligence (AI) has encouraged its incorporation into EBP, including as a tool for clinical nurses to further increase efficiencies in care provision and decision-making. However, AI integration poses challenges in terms of both care practices and ethics. This article was designed to explore the various applications of AI in EBP, emphasizing sustainability alongside ethical, institutional, and technological issues. While AI can improve care efficiency and quality, it also introduces risks such as data errors, algorithmic bias, privacy concerns, intellectual property issues, access inequities, and ethical accountability concerns. Without transparency and oversight, large language models have the potential to exacerbate health disparities and resource gaps. To achieve the core values of improving care quality and patient safety through technology, integrating AI into EBP requires the building of a robust framework that is clinically practical, regularly updated with new algorithms, and includes monitoring systems and ethical governance. Ultimately, the harmonization of AI capabilities and care principles may be expected to achieve healthcare that is more resilient, value-driven, high-quality, and sustainable.