How we can cope with big health data challenges?
1. Missing data
IT officers should cooperate with the health care officer to well and properly organized design the EMR supporting the collection of health data and preventing missing data. Also, increasing awareness in registering data in health care officer is an important milestone. If the data collection system works properly, it will reduce the number of missing data significantly. In addition, the statistical methods (eg. imputation techniques, mixed-effects regression model, generalized estimating equations, inference ) are one of the solutions to cope with unplanned missing data.

2.Selection bias
There are many different factors in health care in different countries. Officers using big data for analytic information should aware of these limitations. But, we can reduce these limitations by using statistical techniques including propensity score analysis, instrumental variable analysis, and Mendelian randomization.

3.Data analysis and training
Increasing knowledge of researchers about data analytics and statistical method is one of the solutions for this problem. Another is having support from data scientists and statisticians by recruiting them to the organization.

4.Privacy and ethical issue
Law enforcement about health data management considering both personal privacy and public benefits must be legislated to prevent misapplication of personal health data.