With the rapid development of artificial intelligence technology, task-based dialogue systems have become a hot research direction in the field of human-computer interaction. The pipelined approach is regarded as a classical design framework, playing a significant role in the research and application of task-based dialogue systems. The research progress in pipelined task-based dialogue systems was overviewed, with a specific emphasis on their application in the medical field. Firstly, the basic principles, evaluation metrics and commonly used datasets of each module of pipelined dialogue systems were introduced. Then, the important advances made by deep learning techniques in the research of pipelined dialogue systems in recent years were sorted out, and the advantages and disadvantages of the models used were further summarized. Subsequently, the application of pipelined dialogue systems in the medical field was specifically focused on, and the requirements and challenges of medical dialogue systems were discussed. Finally, the full paper was summarized and future research directions and trends were outlined.