Research And Application Of SPAM Algorithm In Medical Insurance Data Mining

In recent years,with the extensive application of medical insurance information,the medical insurance industry has accumulated a lot of data.The data of insurance information has been providing a huge support for medical insurance research.At the same time,medical insurance data has the advantages of wide span and long accumulation time,which could bring more opportunities for sequence pattern mining.Therefore,the use of data mining technology to find valuable information in medical insurance data is one of the hottest researches.Sequence pattern data mining is to discover the frequent sub-sequences from the sequence database and use it as a mode.In this way,the hidden,useful and undiscovered data can be found and applied to medical insurance and hospital management.Sequence pattern mining SPAM(Sequential Pattern Mining using A Bitmap Representation)algorithm uses bitmap to represent the database,the advantages of which include small storage space in running process and supporting parallel technology to calculate the number of support.Thus,the proposed method could improve the efficiency and decrease the running time.In this paper,we choose a better SPAM algorithm in sequence pattern mining to research on the medical insurance.It can be applied to the data analysis and application environment of medical insurance,to obtain the diagnosis and treatment patterns of different diseases in medical insurance data,and to get more information from the mining results.In this paper,the main work can be summarized as follows:1.Medical insurance data cleaning.The work of data cleaning is to carry out and solve the uncorrected,redundant,and repeated data in medical insurance database,such as drug name inconsistency,duplicated records,incomplete drug type data and etc.2.Diagnosis and treatment analysis by using SPAM algorithm.The SPAM algorithm is used to mine the data.And the result of the sequence pattern set is used to analyze the drug data from three aspects: sequential pattern set analysis,abnormal phenomena analysis of drugs and commonly used drug analysis.We try to find out the user's medical behavior and the doctor's diagnosis mode or rule.3.Application of SPAM algorithm in medical cost analysis.the SPAM algorithm is used to mine the medical expenses,and the result of the sequence pattern set is used to analyze the medical expenses from three aspects:Drug cost analysis,medical expenses type analysis and comparative analysis of medical expenses.Thus,we can get valuable information,in order to serve the people better.