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Application scenario
Smart Hospital (Medical) Big Data Visualization
Medical big data itself has both distinct big data characteristics and typical industry characteristics; it is a mine that can generate huge wealth one after another. Its service objects can be residents, medical service institutions, research institutions, medical insurance management institutions, public health management departments, etc. China has problems such as a huge population base, serious waste of medical resources, shortage and unreasonable allocation of medical resources, too fast growth of medical expenditure, and weak development of commercial insurance. The applicable scenarios of medical big data are rich and can be deeply mined.
Facing challenges
Solution
Overall planning, to build a comprehensive business solution
Smart Hospital (Medical) Big Data Visualization
Application value
Clinical Decision Support
Clinical decision support is a medical big data application system with daily medical diagnosis and treatment data as the core and patient data as the auxiliary. Relying on a large number of electronic medical records to build a clinical decision support system, and supporting daily medical diagnosis business with a large amount of historical diagnosis and treatment data, reducing diagnosis and treatment errors and improving diagnosis and treatment efficiency.
Medical Drug and Device R&D
Medical drug and device R&D takes R&D data as the core and diagnosis and treatment data, patient data, and payment data as the auxiliary, providing big data informationization construction for commercial decision analysis for pharmaceutical companies, medical device manufacturers, and pharmaceutical and medical device distributors. It not only provides decision basis for sales behavior from data such as sales volume and customer feedback, but also provides in-depth and specialized improvement opinions on drug targeting research and wearable feedback from the particularity of medicine itself.
Chronic Disease Health Management
Chronic disease health management relies on patient data that can be obtained from modern intelligent devices, and through corresponding big data mining, realizes big data applications for chronic disease maintenance that cannot be cured for life and require long-term treatment. On the one hand, big data chronic disease prevention can be carried out based on the patient's historical medical history and family genetic history; on the other hand, long-term chronic disease management can be carried out based on the patient's behavioral sensory data and the chronic disease database.
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