Interpretation and Implementation Prospects of the Expert Consensus on Clinical Application for Patient-controlled Analgesia Based on Intelligent Analgesia Technology
The transition from conventional patient-controlled analgesia (PCA) to artificial?intelligence-assisted patient-controlled analgesia (Ai-PCA) represents an innovative model for analgesia management. Clinicians utilize AI-enabled PCA devices to deliver individualized analgesia according to patients’ pain intensity and physical status. This review interprets the 2024 Chinese Expert Consensus on Clinical Application of Patient-controlled Analgesia, a landmark document for innovative analgesic strategies. We summarize the historical evolution of postoperative PCA and Ai-PCA, the rationale for consensus development, clinical implementation details, quality management frameworks, and future directions of Ai-PCA. Measures to improve Ai-PCA performance and perioperative pain management are analyzed, highlighting priorities for further clinical translation. As a core clinical specialty reflecting comprehensive hospital service capacity, anesthesiology benefits greatly from artificial intelligence. Integrating AI into pain medicine ushers in an era of big-data-driven preventive analgesia, which can improve patient comfort and satisfaction, enhance enhanced recovery after surgery (ERAS), and guide clinicians toward standardized, rational pain therapy.
Authors
- Qinjun Chu (ORCID: https://orcid.org/0009-0008-1188-4151)
- Bin Zheng (ORCID: https://orcid.org/0000-0002-6580-8233)
- 佘守章
- Hanzhong Cao (ORCID: https://orcid.org/0009-0006-5901-6260)
- Weifeng Yu
- Wenqi Huang
Institutions
- Sun Yat-sen University (CN)
- Nantong University (CN)
- Wenzhou Medical University (CN)
- First Affiliated Hospital of Wenzhou Medical University (CN)
- Nantong Tumor Hospital (CN)
- Guangzhou First People's Hospital (CN)
- The First Affiliated Hospital, Sun Yat-sen University (CN)
- Zhengzhou Central Hospital (CN)
- Guangzhou Medical University (CN)
Publication Details
- Journal
- International Journal of Pain Research
- Published
- 2026-08-27
- DOI
- https://doi.org/10.11648/j.ijpr.20260203.16
- Primary Topic
- Enhanced Recovery After Surgery
- Type
- article
- Field-Weighted Citation Impact
- 0.00