智慧醫工框架下的抗生素用藥量化與抗藥風險管理：以Days of Antibiotic Spectrum Coverage為核心的指標演進與技術整合

Quantification of Antibiotic Use and Resistance Risk Management under a Smart Medical Engineering Framework: Evolution and Integration of the Days of Antibiotic Spectrum Coverage (DASC) Metric

抗微生物製劑抗藥性（AMR）為全球公共衛生之重大挑戰，如何有效量化並管理抗生素使用風險，已成為醫療體系的重要課題。傳統指標如治療日數與定義每日劑量，未能涵蓋抗菌範圍變化，限制其對降階治療與廣效性抗生素監控的敏感性。近年提出之抗菌範圍天數指標，整合抗菌範圍評分與實際用藥日數，能更具體反映病患所承受的抗菌選擇壓力。本文採用回顧式文獻分析與系統整合設計，探討抗生素抗菌範圍天數之演進與應用挑戰，並提出一套智慧醫工導向之整合架構，結合自動化資料串接、抗菌範圍分數本土化、人工智慧風險預測與臨床決策支援系統整合，提升DASC的可操作性與臨床實用價值。期望本架構有助於建立具前瞻性之抗藥風險治理機制，促進精準抗生素管理於台灣醫療體系之落實。

Antimicrobial resistance (AMR) poses a critical challenge to global public health. Effective antibiotic stewardship requires precise tools to quantify antibiotic use and assess antimicrobial pressure. This study explores the development and clinical utility of the Days of Antibiotic Spectrum Coverage (DASC) metric, which integrates the breadth of antimicrobial activity with days of therapy. A narrative review and integrative systems design approach were adopted to evaluate the applicability and limitations of DASC. We propose a smart biomedical engineering framework that incorporates automated data integration, localized ASC calibration, AI-based resistance risk prediction, and integration with clinical decision support systems. This architecture aims to enhance DASC’s sensitivity, interpretability, and clinical utility. DASC has the potential to serve as a core indicator for antimicrobial stewardship, enabling real-time, precision-driven decision support. Its successful implementation will require interdisciplinary collaboration and a robust information system infrastructure.