Method of coping with those challenges (Big Health Data or EHR)
Solving the missing data
To reduce missing data, I think standardizing the definitions and variables across data systems so data are collected consistently and shared more easily. Improve data quality by relying on structured electronic health records with clearly defined key variables and conducting regular data audits and generating missing-data reports, followed by clear and practical action plans. In addition, provide continuous orientation and engage clinicians and data collectors to reduce avoidable data gaps.
Reducing the selection Bias
Addressing selection bias by developing a clear and predefined data analysis plan that specifies inclusion criteria and essential variables in advance is vital. Apply appropriate statistical methods to adjust for confounding factors. Because most big health data are observational, it is essential to interpret findings cautiously and use them mainly to generate hypotheses rather than to directly inform clinical decision-making.
Improve the skills of Data Analysis and provide training
Analyzing complex big data such as the example from cardiovascular research requires strong multidisciplinary collaboration. Bringing clinicians, statisticians, and data scientists together to improve both the quality and relevance of analyses is a must. Also develop shared analytical models supported by targeted training to ensure accurate analysis and meaningful interpretation. Continuous capacity building for those who are responsible is essential.
Interpretation and Translational Applicability of Results
Prioritize clinically interpretable models so results remain useful in real-world cardiovascular care. By involving clinicians in model development and validation, I ensure that findings align with actual clinical workflows and can be responsibly translated into practice.
Privacy and Ethical Issues
Develop a data-sharing policy and strengthen data governance to protect patient privacy. To ensure the use of big health data balances public benefit with individual rights, apply secure access controls, ethical oversight mechanisms, and transparent data-use policies.