Data Analysis of Hospital Management System and Provide Personalize Hospital Services

Computer Engineering

These massive quantities of health data, which can be regarded as big data ,hold the promise of supporting a wide range of medical and healthcare functions ,including clinical decision support, disease surveillance, and population health management when health data analysis is performed properly. The analytical challenges that come with the availability of big health data are many and can be summarized as the integration of multi-modal data coming from different sources to generate a semantically consistent dataset. Health is generating large volumes of data that can provide invaluable insights into clinical and operational aspects of healthcare delivery. There is a general lack of specialized and integrated health data analytics platforms that offer technical methods to support the entire health data analysis pipeline i.e. health data selection, integration, analysis, visualization and sharing. This paper proposes the technical architecture of a health data analytics platform that offers a technical solution for analyzing big health data originating from multiple sources with heterogeneous terminologies and schemes .A key aspect of the architecture is data standardization, where we have used SNOMED-CT as a terminology standard to standardize health data from multiple sources.

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