From Patient-Controlled Analgesia to Artificial Intelligence-Assisted Patient-Controlled Analgesia: Practices and Perspectives - Wang, Rui; Wang, Shaoshuang; Duan, Na; Wang, Qiang (Frontiers in Medicine, 2020)
Pain relief is the major concern of patients who underwent surgery and is an eternal pursuit of anesthesiologist. However, postoperative pain management is far beyond satisfactory although the past decades has witnessed great progress in the development of novel analgesics and analgesic techniques. Cochrane systemic review showed that patient-controlled analgesia (PCA) achieved better pain relief and greater patient satisfaction compared with traditional “on-demand” parenteral analgesia, suggesting that it might be the manner of analgesia implementation that matters for effective postoperative pain management. A wireless intelligent PCA (Wi-PCA) system that incorporated remote monitoring, intelligent alarm, intelligent analysis and assessment of the PCA equipment as well as automatic recording and reserving key information functions under a wireless environment was introduced in our department since 2018. The practice showed that the Wi-PCA system significantly reduced the incidence of moderate to severe postoperative pain and relevant adverse effects, together with shortened hospital stays and improved patients’ satisfaction with postoperative pain relief. Nevertheless, for both traditional and Wi-PCA, analgesics are only administered when pain happened, leaving room for better postoperative pain management. With the rapid development of machine and deep learning algorithms, artificial intelligence (AI) is changing the mode of clinical decision making. Integrating the big data collected by state-of-art monitoring sensors, the Internet of things and the AI algorithms, an AI-assisted PCA (Ai-PCA) maybe the promising future direction of postoperative pain management.