Construction of patient service system based on QFD in internet of things

In recent years, as the basic medical science is improved, the prevention and treatment of bedsore have made great progress. However, from the incidence rate of bedsore worldwide, its downward trend is extremely weak, so the nursing of a bedsore is still a major problem in the medical field. To explore the construction of patient service system based on quality function deployment (QFD) in the Internet of Things (IoT) environment, in this study, with the support of IoT technology, deep learning algorithm and QFD method are used to build patient service model to achieve the detection and nursing reminder of patients' physical condition. The basic framework of patient service system is constructed, and the system performance is simulated and analyzed in the simulation environment. The results show that when the data collection and analysis of health monitoring, functional analysis and the functional architecture of IoT are further carried out, it is found that the service system built in this study is more standardized, and it can monitor the physiological data of patients who are bedridden for a long time and cannot turn over in real time, so as to have a preliminary understanding of the patients' physical condition. Through the results of the service system, patients can get personalized care that varies from person to person, thus reducing the pressure of medical staff, and doctors can have a clearer real-time understanding of patients' physical condition. Therefore, in this study, the patient service system constructed has a timely avoidance effect on bedsore and achieves the expected demand, to provide an experimental basis for the service treatment of patients in the later medical industry.