Application of artificial intelligence system based on control theory feedback model in ultrasound diagnosis and treatment medical insurance payment

Abstract

Objective To analyzes the optimization function of artificial intelligence system based on control theory feedback model applied to medical insurance payment. Methods Aiming at the unclear category of ultrasonic diagnosis and treatment, an artificial intelligence system for ultrasonic diagnosis and treatment medical insurance payment was developed through using control theory feedback model by our team, and the differences before and after application of this system was compared. A comprehensive collection of abnormal data on medical insurance fund payments was conducted using the hospital information system (HIS) , picture archiving and communication system (PACS) , and the medical insurance payment data platform, covering the period from January 2020 to December 2023. Quantitative analysis methods were employed to analyze both the original abnormal medical insurance data and theimproved data following the implementation of the control theory feedback system. Results A total of 46 617 records of original abnormal medical insurance data were collected. Among these, excessive charges accounted for 7 736 cases, totaling 386 800 yuan; expanded scope charges for 4 877 cases, totaling 68 016 yuan; duplicate charges for 28 976 cases, totaling 1 028 586 yuan; decomposed charges for 1 321 cases, totaling 92 470 yuan; over-standard charges for 3 651 cases, totaling 255 525 yuan; and category switching for 56 cases, totaling 560 yuan. After the improvement with the control theory feedback system, there were 492 records of abnormal medical insurance data, including 135 cases of excessive charges, 4 cases of expanded scope charges, 281 cases of duplicate charges, 60 cases of decomposed charges, and 12 cases of over.standard charges, with no occurrences of category switching. Compared with the original abnormal medical insurance data, the abnormal data after the improvement significantly decreased, along with a significant reduction in medical insurance payment amounts. Conclusion The artificial intelligence system for ultrasound diagnostic and treatment based on the control theory feedback model can significantly reduce unnecessary examinations, lower medical insurance fund payments, enhance patients’satisfaction, decrease the misjudgment rate of diagnosis related groups (DRG) , and improve the work efficiency of medical staff.

Keywords

• ultrasound diagnostic and treatment
• medical insurance payment mechanism
• artificial intelligencesystem
• control theory feedback model
• medical quality management