Disclosure(s): No relevant financial relationship(s) to disclose.
Disclosure(s):
Vitaly Herasevich, MD, PhD, FCCM: No relevant financial relationship(s) to disclose.
The architecture of electronic health record (EHR) data is significantly more complex than that of single-purpose newer databases. The development of modern electronic medical records (EMR) can be traced back almost 50 years. This long history introduces challenges in terms of using multiple standards or no standards at all, as well as the need to filter out a massive amount of non-clinical information in order to extract the data that truly matters. The first step in creating an informatics structure for data management is to establish clear guidelines and standards. This involves defining the necessary data elements and standardizing their formats across the organization. By doing so, the data can be easily compared and analyzed, facilitating research efforts and enabling data interoperability. Overall, creating an informatics structure for data management involves addressing the complexities of EHR data architecture by establishing standards, filtering out irrelevant information, and implementing a HIPAA-compliant layer. This comprehensive approach paves the way for efficient data analysis, enabling valuable research opportunities while upholding patient privacy and security. In this session, the speaker will outline the necessary steps to create an informatics structure for effective data extraction and management. This structure should focus on standardization and ensure compliance with HIPAA regulations, particularly when it comes to data usage for research purposes. By implementing this structure, healthcare organizations can establish a solid foundation for managing and utilizing their EHR data for research and analysis purposes.
