The medical foundation model performs efficient processing and pattern recognition of complex medical data based on a deep neural network architecture, providing a new type of decision support for intelligent medical care. It is necessary to systematically analyze the technologies and application of the medical foundation model, thus to identify the development directions and challenges and improve the capabilities of the medical care sector in medical text writing, medical image recognition, medical equipment research and development, and medical education using the medical foundation model. This study sorts out the technology paradigm and application scenarios of the medical foundation model and proposes a technology system and an evaluation system for the model. The technology system is composed of a base layer, a model layer, an application layer, and a common module. The evaluation system involves the establishment of an evaluation index system, dataset range and question types, model alignment methods, and model evaluation platforms. Moreover, application challenges of the medical foundation model are identified in terms of data security, technical risks, implementing challenges, and ethics. Furthermore, the following countermeasures are suggested: (1) ensuring data security through government guidance, (2) accelerating basic theoretical research to address technic risks, (3) focusing on application scenarios to cope with implementing challenges, (4) improving the ethics regulating mechanism, and (5) perfecting the public service system to create an innovation ecosystem, thereby accelerating the innovative development of the medical foundation model and promoting the high-end, intelligent, and green development of intelligent medical care in China.