Perioperative drug-related rare adverse reactions are often characterized by acute onset, high risk, and unpredictable, involving complex physiological and genetic factors. Currently, most perioperative pharmacovigilance relies on clinical monitoring and real-time data reporting by medical teams. However, due to scattered data and the masking of symptoms by anesthetics and pain medications, it is difficult to predict rare adverse reactions accurately and promptly. This paper systematically reviews the latest advancements in the integration of digital and intelligent technologies across various fields. Based on real-world data, our research team had leveraged digital-intelligence fusion technologies to deeply integrate big data with artificial intelligence, thereby constructing a standardized anesthesia-specific database. This enabled dynamic monitoring of vital signs, individualized risk prediction, and comprehensive analysis of multimodal data in real-world studies, providing an innovative solution for perioperative pharmacovigilance. The aim of this paper is to enhance the personalization and intelligence of perioperative drug safety management, thereby offering more effective protection for patient medication safety during the perioperative period.

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