Using Association Rules Data Mining to Explore over Proof Medical Costs Based on Apriori Algorithm

Objective:To analyze the composition of patients' medical costs,to explore whether the composition of medical costs is reasonable,to find the causes of over proof medical costs and to help the hospital managers to control medical costs.Methods:Use 3/4 percentile of the diagnosis related group medical costs as the threshold of over proof medical costs,distinguish the standard medical costs and over proof medical;use Apriori Algorithm in the association rules method of data mining,to find the condition attributes which have strong association with the over proof medical costs.Results:In the respiratory system disease,1/4 of pationts with the over proof medical costs had occupy over 40% medical resources.There were 4 significant association rules in the association rule model,they could monitor 10.7% patients have over standard medical costs.The possibilities of developing over standard medical costs with the 4 rules were 2.47,2.36,2.30 and 2.29 times more than before,respectively.Conclusion:The quality control department in the hospital may use the strong association rules to control medical costs,to pay more attention to the patients suit with these rules.In the precondition of satisfying the medical demand of patients,avoid situation of over proof medical costs and enhance the prevention of medical costs from happening.