Comprehensive Review on Personalized Pain Assessment and Multimodal Interventions for Postoperative Recovery Optimization

Abstract

Jingying Xu,1,* Xiaona Liu,1,* Jinyan Zhao,1 Jingjing Zhao,2 Hao Li,1 Huanhuan Ye,2 Shuang Ai2 1Department of Rehabilitation Medicine, Joint Logistics Support Force No. 964 Hospital of People’s Liberation Army of China, Changchun, Jilin, 130000, People’s Republic of China; 2Department of Outpatient, Joint Logistics Support Force No. 964 Hospital of People’s Liberation Army of China, Changchun, Jilin, 130000, People’s Republic of China*These authors contributed equally to this workCorrespondence: Shuang Ai, Email [email protected]: Postoperative pain management is an important determinant of patient recovery, as it directly influences rehabilitation efficiency, hospitalization duration, and the risk of postoperative complications. Despite its significance, traditional pain management strategies often fail to adequately address individual variability and the multidimensional nature of pain, thereby limiting their effectiveness. To address these limitations, we designed this comprehensive narrative review to systematically summarize relevant literature published between 2000 and 2024, from databases such as PubMed and Web of Science, with a particular focus on personalized pain assessment and multimodal interventions to optimize postoperative recovery. Personalized pain assessment, guided by the biopsychosocial model, captures the biological, psychological, and social dimensions of pain, offering a more comprehensive and individualized evaluation of patient needs. In parallel, multimodal interventions, which integrate pharmacological and non-pharmacological strategies, are designed to target multiple pain mechanisms simultaneously, thereby enhancing analgesic efficacy while minimizing adverse effects. Emerging evidence indicates that combining personalized pain assessment with multimodal interventions can significantly improve clinical outcomes, as demonstrated by reductions in postoperative pain scores by approximately 20– 30%, shorter hospital stays by 1– 2 days, and decreased opioid consumption by 25– 40%. Notable clinical applications supporting these findings include the use of dynamic pain monitoring devices, virtual reality-based therapies, and prehabilitation programs to facilitate recovery. Building upon these findings, this review further discusses the theoretical foundations underlying personalized pain management, explores its clinical applications, and examines the practical challenges associated with its implementation. Additionally, future directions are proposed, including the development of AI-driven pain assessment tools, the promotion of interdisciplinary collaboration, and the establishment of standardized clinical protocols. Collectively, these advancements support the potential of personalized, multidimensional strategies to improve postoperative outcomes and enhance overall patient satisfaction.Keywords: personalized pain assessment, multimodal interventions, postoperative recovery, pain management, enhanced recovery

Keywords

• Personalized pain assessment
• Multimodal interventions
• Postoperative recovery
• Pain management
• Enhanced recovery