ObjectiveTo summarize the research status of intelligent patient monitoring and risk warning, and provide reference and enlightenment for promoting the construction of intelligent monitoring and management platform of clinical patient risk.MethodThe literatures about patient monitoring and risk warning at home and abroad in recent years were reviewed.ResultsAt present, the research at home and abroad mainly focused on the retrospective construction of the prediction model of severe complications of inpatients by using the electronic medical record database. The clinical decision support system based on real-time vital signs and dynamic electronic medical record data was still in the early development stage, and there was no mature product with high market share.ConclusionsThe construction process of structured electronic medical record system should be further strengthened, and the fully integrated clinical decision support system and artificial intelligence self-learning system should be the key research and development direction in the future, so as to promote the deep integration of big data and artificial intelligence technology with clinical scenes.
Wearable monitoring, which has the advantages of continuous monitoring for a long time with low physiological and psychological load, represents a future development direction of monitoring technology. Based on wearable physiological monitoring technology, combined with Internet of Things (IoT) and artificial intelligence technology, this paper has developed an intelligent monitoring system, including wearable hardware, ward Internet of Things platform, continuous physiological data analysis algorithm and software. We explored the clinical value of continuous physiological data using this system through a lot of clinical practices. And four value points were given, namely, real-time monitoring, disease assessment, prediction and early warning, and rehabilitation training. Depending on the real clinical environment, we explored the mode of applying wearable technology in general ward monitoring, cardiopulmonary rehabilitation, and integrated monitoring inside and outside the hospital. The research results show that this monitoring system can be effectively used for monitoring of patients in hospital, evaluation and training of patients’ cardiopulmonary function, and management of patients outside hospital.