基于大数据分析的中医门诊医疗诊费点阵模型构建

Construction of Dot Matrix Model of Medical Diagnosis and Treatment of Traditional Chinese Medicine Outpatients Based on Big Data Analysis

目的:为了有效及时地分析中医诊疗门诊费用的异常情况。方法:基于已有的中医大数据平台采集了全省多家中医院的30多万条门诊电子病历数据,构建医疗诊断费用点阵模型。采用基于距离指标的异常数据挖掘技术对预处理后的数据进行聚类分析,挖掘出数据记录中的噪点,研究费用离群点的异常行为。结果:实验按照疾病分类,以肝病3万多条病历数据为例进行诊疗费用偏离值检测,分离同病种的医疗异常费用数据集,找出异常收费项目点。结论:提供异常费用点阵图,中医医院门诊费用管理实现可视化和提醒,为医生临床门诊的用药和合理收费提供参考,从而督促医生坚持合理用药,合理检查、合理治疗、合理收费。

Objective:For effective analysis of the abnormal clinical diagnosis and treatment fee.Methods:More than 300,000 electronic medical record data of outpatient from many Chinese hospitals in Sichuan province were collected,and a medical fees lattice model was constructed.The abnormal data mining technology based on distance index was used to cluster the preprocessed data,and the noise in the data record was mined to study the abnormal behavior of outliers.Results:According to the classification of diseases,the experiment used the data of more than 30,000 medical records of liver diseases as an example to detect the deviation of medical expenses,and to isolate the medical abnormal cost data sets of the same disease and find out the abnormal charging items.Conclusion:Through the abnormal cost bitmap,provide visualization and reminder for outpatient management of Chinese medicine hospitals,provide reference for doctors'clinical medication and reasonable charges,and urge doctors to insist on rational drug use,reasonable examination,reasonable treatment and reasonable charges.