Medical insurance fraud refers to the behavior of medical insurance fund or medical insurance coverage, which causes the loss of medical insurance fund through the method of deliberately fabricating and fictitious facts. Effective identification of health insurance fraud is of great significance to the rational use of health insurance funds. This study uses BP neural network to realize the active identification of health insurance fraud, and uses logistic regression analysis to improve the neural network model and reduce the interference of the weak factor to neural network identification. In addition, to deal with the scarce problem of fraudulent data, the model of neural network simulation function is used to train neural network. The empirical evidence shows that this method has better identification ability for health insurance fraud.