基于改进聚类分析算法的医院DIP智能管理平台异常数据监测研究

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中图分类号：R197.324；TP311.52

文献标志码：A      文章编码：1672-7274（2025）08-0016-03

Research on Abnormal Data Monitoring of Hospital DIP Intelligent Management Platform Based on Improved Clustering Analysis Algorithm

LI Xiaogang （Zhongshan Hospital Affiliated to Xiamen University，Xiamen 361ooo，China）

Abstract： This article proposes an improved clustering analysis method based on ant colony algorithm to addressthe shortcomings oftraditional clustering analysis algorithms in scenario applications.The DIP platformof hospitals has complex data，covering various aspects such as patient diagnosis and treatment，expenses，and medical insurance.Theexistence of abnormal data seriouslyaffects the scientificityof hospital management and decisionmaking.Traditionalclusteringalgorithmsaresensitivetodata distribution，relyoninitial values，andhave limitations in high-dimensional data processng.This study introduces ant colony algorithmand optimizes the clustering process by utilizing its pheromone mechanism and search characteristics.The experimental results show that seting the embedding vector dimension of the hospital DIP inteligent management platform parameters to32，the data byte length to 40，andthe number of hidden neurons to 64，hasa high accuracy in monitoring and identifying abnormal data on the hospital DIP intelligent management platform.

KeyWords： improved clusteringanalysis algorithm; hospitalDIP intellgent management platform; abnormal data monitoring; monitoring accuracy

随着医保支付方式改革在全国全面推广，医院病种分值付费（DIP）智能管理平台在帮助医院实现DIP支付方式改革、助力医院精细化管理等方面发挥着至关重要的作用。（剩余4019字）