Objective To construct an intelligent recognition,prevention,and control system for infectious disea-ses and multidrug-resistant organism infections,aiming at improving the efficacy of full-process management,and to evaluate its application effects.Methods Based on personalized logic parsing rules that accurately reflect the infec-tion status and transmission risks in real-time,an intelligent recognition,prevention,and control system with func-tions of automatic recognition,dynamic labeling,real-time sharing,early warning,and visual guidance was estab-lished.Patients undergoing invasive diagnostic and therapeutic procedures in two departments of a tertiary first-class hospital from October 2023 to May 2024 were selected as the research subjects.The differences in recognition,pre-vention,and control efficacy before and after the application of the system were compared using a self-controlled method,with traditional manual management as the control group and intelligent system management as the experi-mental group.Results A total of 2 146 patients were included in the analysis.The recognition,prevention,and control rate and the accuracy rate of recognizing infected individuals using the intelligent system were enhanced sig-nificantly compared with those using manual mode(improved from 5.3％and 72.4％to 100％,respectively),with statistical significance(both P＜0.001).The median early warning time for infection information reached 85.20 days,with 100％early warning achieved.The average time spent by medical staff on infection information recogni-tion and management was reduced by 4.71 hours per day.Conclusion The intelligent system constructed in this study significantly improves the effectiveness of full-process management in recognition,prevention,and control of infectious diseases and multidrug-resistant organism infection,effectively reduces the risk of cross-infection,and en-hances the efficiency of diagnostic and therapeutic services.

Objective To construct an intelligent recognition,prevention,and control system for infectious disea-ses and multidrug-resistant organism infections,aiming at improving the efficacy of full-process management,and to evaluate its application effects.Methods Based on personalized logic parsing rules that accurately reflect the infec-tion status and transmission risks in real-time,an intelligent recognition,prevention,and control system with func-tions of automatic recognition,dynamic labeling,real-time sharing,early warning,and visual guidance was estab-lished.Patients undergoing invasive diagnostic and therapeutic procedures in two departments of a tertiary first-class hospital from October 2023 to May 2024 were selected as the research subjects.The differences in recognition,pre-vention,and control efficacy before and after the application of the system were compared using a self-controlled method,with traditional manual management as the control group and intelligent system management as the experi-mental group.Results A total of 2 146 patients were included in the analysis.The recognition,prevention,and control rate and the accuracy rate of recognizing infected individuals using the intelligent system were enhanced sig-nificantly compared with those using manual mode(improved from 5.3％and 72.4％to 100％,respectively),with statistical significance(both P＜0.001).The median early warning time for infection information reached 85.20 days,with 100％early warning achieved.The average time spent by medical staff on infection information recogni-tion and management was reduced by 4.71 hours per day.Conclusion The intelligent system constructed in this study significantly improves the effectiveness of full-process management in recognition,prevention,and control of infectious diseases and multidrug-resistant organism infection,effectively reduces the risk of cross-infection,and en-hances the efficiency of diagnostic and therapeutic services.