從感測到決策──巧用科技提升護理專業判斷力

From Sensing to Decision: Leveraging Technology to Enhance Nursing Clinical Judgment

隨著人工智慧、物聯網與感測技術在醫療照護領域的快速滲透，護理臨床第一線正經歷從「感官驅動」到「數據驅動」的結構性轉變。可穿戴感測器、生成式人工智慧與遠距監測系統等工具使生理數據的取得更加即時且連續；然而，數據量的激增並不等於臨床判斷品質的提升，當過多的警示與資訊湧入工作流程，反而可能引發認知超載與警報疲勞。本文從「感測—整合—決策」的脈絡出發，探討感測科技如何擴展護理師的臨床觀察能力，臨床決策支援系統如何協助將零散數據轉化為可行動的照護判斷，以及護理師在科技輔助下所需具備的數據素養、臨床整合能力與人本照護精神。文中亦討論科技照護衍生的倫理議題，包括資料隱私、演算法偏差與過度依賴風險，最後提出護理教育與實務面向的具體建議，期望為智慧醫療時代下的護理專業發展提供參考方向。

With the rapid integration of Artificial Intelligence (AI), the Internet of Things, and sensing technologies into healthcare, the nursing frontline is undergoing a structural transformation from“sensory-driven”to“data-driven”practice. Tools such as wearable sensors, generative AI, and remote monitoring systems enable the real-time and continuous acquisition of physiological data. However, the increase in data volume does not inherently equate to improved clinical judgment. When excessive alerts and information infiltrate the workflow, these data may trigger cognitive overload and alarm fatigue. In this article, the“Sensing-Integration-Decision”framework is adopted to explore how sensing technologies expand the clinical observation capabilities of nurses and how clinical decision support systems facilitate the conversion of fragmented data into actionable care insights. Also, the essential competencies required of nurses in tech-assisted environments, including data literacy, clinical integration skills, and the core spirit of humanistic care, are explored. Furthermore, ethical issues arising from technology-mediated care such as data privacy, algorithmic bias, and the risk of over-reliance, are addressed. Finally, concrete recommendations for nursing education and practice are provided to guide professional development in the era of smart healthcare.