Electronics health records, knowledge management, informatics and the potential to differentiate health disparities

EHRs are a primary data source used to differentiate public health disparities. The value of EHR's is limited by technical complications of normalizing and merging data with secondary public health data sources. To overcome this difficulty, we created a process to merge healthcare and secondary public health information into a cohesive de-identified public health research system. We use methods developed for biomedical informatics research and demonstrate the value of these methods to develop evidence associated with health disparity. Our initial effort repurposes and merges EHR data to create a Milwaukee Area Public Health Research Database (MAPHRD) using a cloud computing enabled ‘i2b2' platform. A combination of de-identified health records coupled to clinical ‘avatar' health records (fictitious records that reflect actual data and are statistically consistent with patient populations) are used to demonstrate the process. The MAPHRD HIPAA compliant, automated pipeline can be customized and anonymizes and transforms EHR data into i2b2 standardized format following federal HIT standards.

The rapid expansion of EHRs provides opportunity to calibrate and quantify outcomes of standardized health practice. “Meaningful use” outcome metrics can then be computed and used to quantify health disparities thereby providing evidence to modify public health policy to minimize or remove the factors causing the disparity. Our system and method produces standard data from complex medical care EMR data and defines relationships between complex EMR data elements and public health outcome objectives correlated to the recently released HHS meaningful use criteria of ‘data mining key health issues and reporting public health measures'.