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194 Journal of Library Science in China, Vol.10, 2018

disease management. It is necessary to establish a “health-oriented big health concept” as an
overall response to a wide range of health-influencing factors, and create a “knowledge-prevention-
medical-care-foster” integrating Smart Health models in health tracking, prediction, disease
prevention, patient health management and personalized treatment in an all-round and life-cycle
way. However, there exists a common problem: the spatial distribution, composition structure,
type format and representation of the massive, heterogeneous and multi-source health data are
becoming more and more complicated and make medical information management particularly
difficult. How do we effectively obtain, organize, query and analyze a large number of health data
and successfully apply them to modern medicine?
This study aims to apply knowledge management, knowledge service theory and methods
from the field of information resources and management to the field of Smart Health through
constructing the Public Health Knowledge Base and Personal Health Big Data Management
Platform to integrate decentralized personal health data, medical data, and smart health knowledge.
On the basis of grasping the connotation, orientation, objectives and system structure of smart
health knowledge management, the Public Health Knowledge Base is designed based on the
construction of Knowledge Graph in an open network environment, which provides decision
support for smart health service. The process can be divided into steps of health information
collection, health knowledge extraction, representation, organization, assessment, and fusion.
In addition, the Personal Health Big Data Management Platform is constructed to monitor the
physical state of the public, assist doctors in making accurate diagnosis and medication decisions,
and even remind patients to quit bad habits. On this foundation, the smart health knowledge
service mechanism is constructed based on user need and health portraits. The coarse-grained
matching based on ontology, fine-grained matching based on multiple knowledge fusion, and user
portrait construction pattern are proposed to provide smart health knowledge service for the public,
medical and nursing staff, and professional medical institutions.
In summary, constructing the Public Health Knowledge Base, the Personal Health Big Data
Management Platform and the smart health knowledge service mechanism can facilitate monitoring
and understanding health status in real time, and push smart health knowledge to achieve self-
health management, although the research we have done is basic and theoretical exploration.
In order to realize the Health China strategy of “constructing and sharing, the health of whole
people”, it is necessary to raise the Smart Health to the national strategic level. Closely combining
the great advantages of intelligent city, standing at the strategic height, Smart Health must make
breakthroughs in four aspects: ① Strengthening the construction of think tanks in the field of
Smart Health; ② Establishing Standards for Smart Health Data and enhancing healthcare data
collection; ③ Promoting the utilization and sharing of personal health big data; ④ Emphasizing
user demands and forming a smart health industrial system covering the whole life cycle.