Design and application of a “dual-channel” drug management system based on hospital information system

Currently, the “dual-channel” drug management system has become an important channel for hospital and external supply chain drug management. However, how to achieve more efficient drug management is still the main issue in current drug management. Therefore, in order to achieve more efficient drug management. A new “dual-channel” drug management system based on hospital information system was proposed, which uses deep bidirectional network and convolutional recurrent neural network models to identify and manage drugs. At the same time, the new system uses deconvolution and binarization methods to improve the accuracy of drug recognition. The research results show that the accuracy of drug recognition in the model can reach 95.68%, which is 13.33% higher than other models. At the same time, the recall rate was also improved by 14.89% compared to other models. After using the new system, the number of effective image recognitions increased by 10, and the hospital’s revenue growth increased by 7.43%. The new system has better drug management effects and can also improve drug sales efficiency. This has good guiding significance for hospital drug management research.