دانلود رایگان مقاله انگلیسی سیستم تحلیل داده های بهداشت و درمان برای اتحادیه پزشکی منطقه ای در شهر هوشمند - تیلور و فرانسیس 2018

Regional medical unions are practical approaches to deal with the cases that patients crowd in Grade 3 Class A general hospitals in metropolitan cities such as Shanghai, in China. However, electronic medical data analysis exists challenges when patients are referred among different hospitals in the regional medical unions during treatment procedures. In smart cities, demands for medical services provided by smart devises, complicate the environment of medical data analysis. In order to tackle the above problems, in this paper, a healthcare data analysis system for regional medical union is designed to support doctors from different hospitals to assess health conditions of patients in an overall data view. Behaviour patterns are mined from physiological index values. Tags are generated from social networks data to find the hot topics concerned by people living in common region. Experiments are given to illustrate the feasibility of the system in supporting healthcare data analysis.

Conclusion and future work

It has been known that seeing doctor is difficult in China, especially in metropolis such Shanghai and Beijing because too many people would like go to see the doctors in general hospitals directly when they feel ill or worry about their health. Regional medical unions are solutions to solve the problem that patient flows distribute unevenly in these big cities. The contributions of this research are follows. Firstly the organizational model of regional medical union is discussed. In regional medical unions, specialists work with GPs to make treatment plans and dominate the process of treatments. Patients are encouraged to go to general hospitals when they encounter health problems, but would be better referred to GPs in community medical centres for recovery. Secondly in order to support the cooperation of specialists in general hospitals and GPs in community medical centres, a health data analysis platform is proposed to provide integrated patient-centred EMRs, together with individual activity pattern and local social media hot words to support clinical decision-making. The technical details of the platform are discussed. Prototype is developed to ensure what functions should be designed to effectively support the cooperation of specialists and GPs. Finally, several experiments are conducted to show the analysis of individual activity pattern from smart devices. Health data from smart body weight scales and sport data from smart phones are visualized together to illustrate the trend of physiological indexes. Hot words are obtained from local social medias. The relationships among these hot words are linked to reflect the concerned issues potentially matter regional health problems. One future work will be the construction of more accurate models of behaviour pattern and hot words mining for big medical data. Another future work is to design appropriate fog-cloud architecture for regional medical unions to properly balance data processing workloads between smart medical devices and HISs.