Construction and practice of an intelligent management system for preoperative anemia based on multidisciplinary collaboration

[Objective] To improve the efficiency and standardization of preoperative anemia diagnosis and treatment by establishing a systematic intelligent management platform for preoperative anemia. [Methods] A multidisciplinary collaborative model was adopted to develop a preoperative anemia management system that integrates intelligent early warning, standardized treatment pathways, and quality control. The system utilizes natural language processing technology to automatically capture laboratory data and establish evidence-based medical decision support functions. A pre-post study design was employed to compare changes in preoperative anemia screening rates, preoperative anemia intervention rates, reasonable use of iron supplements, and perioperative red blood cell transfusion rates before and after system implementation. [Results] After system implementation, the standardization of anemia diagnosis and treatment significantly improved: 1) Screening effectiveness: The anemia screening rate increased to 50.00% (an increase of 27.24%); 2) Intervention effectiveness: The anemia treatment rate rose to 56.30% (an increase of 14.02%); 3) Treatment standardization: The reasonable use rate of iron supplements increased to 55.33% (an increase of 21.02%); the red blood cell transfusion rate decreased to 18.29% (a decrease of 4.07%), and the amount of red blood cell transfusions was reduced by 291 units. [Conclusion] This system achieves full-process management of preoperative anemia through information technology, significantly enhancing the standardization of diagnosis and treatment as well as intervention effectiveness, providing an effective solution for perioperative anemia management.