The system is capable of handling near 2.5 million electronic
health records for nearly 8,93,000 patients. Tool clearly shows
the management of big data which lead to better lifestyle
choice and better disease outcome. Modules associated with
the system is shown in figure. Unique Patient
intelligence tools are used to tell the relationship between the
factors of lifestyle and treatment. By using the efficient data
mining tools and techniques here they provided the EHR
datasets and social media stuffing for user to follow new
methods and services for protective interferences. Disease
management tools keep track of serious diabetes parameters
like Blood pressure, Blood glucose etc. Additionally it keep
track of diet/nutrition, physical movement and exercises,
medicine, insulin quantity and disease regression or
progression. Social discussion forums are provided to all the
users to have a very healthy discussion on treatment, disease,
experiences, success and challenges. It also provide the safe
and secret platform for users who can get benefit from
available social support. Up-to-date education offers the
health statistics, facts and information, videos, news are
provided from well-known diabetes sites. Creation of digital
representation of the disease is very significant as it would be
more trajectory and manageable by providing the track of
diabetes and life style risk. By providing 652 healthy
recipes and restaurant to the users to have the knowledge of
how to prepare healthy meal, nutrient charts so that increase in
glucose level can be manage. National Health Insurance
Data, the objective of this module is to reply several
frequently asked questions which the diabetes patients and
their caretakers may have with statistical reports extracted
from the Taiwanese National Health Insurance database. All
the questions are sorted and put in the four categories:
prevalence of Diabetes in Taiwan, Out-patient Related
Questions, Inpatient Related Questions, and Medication
Related Questions. Actually sampling is done here in this
module to facilitate patients to choose the questions, based on
the answers patients were categorised as having diabetes and
included in the analysis which will lead to escape growth of
misdiagnosis