When using the current algorithm to detect the discrete data in the medical database, problems such as long execution time, low detection efficiency and low detection rate of discrete points are caused by the lack of data filtering and other processes. Therefore, an algorithm for detecting discrete data in the medical database based on hierarchical deep learning is proposed. Firstly, the dynamic grid method is used to divide the sparse and dense areas in the space, so as to reduce the size of data detection and shorten the detection execution time. Then, the expert knowledge and data attribute value distribution information are integrated through the hierarchical deep learning process, and realize the detection of discrete data in medical database. Experimental results show that this algorithm can accurately complete the detection of discrete data in the medical database in a relatively short time, and has more advantages in application compared with the traditional algorithm.