Profiling and Browsing Functional Level Indicators for Patients with Central Nervous System Injuries Using HL7 Fast Healthcare Interoperability Resources (Preprint)
BACKGROUND Standards-based modeling of electronic health record (EHR) data is important for the interoperability and reusage of data. Combining unstructured data into standard data models in existing clinical data can be problematic because of the different types of systems. OBJECTIVE To overcome this problem, previously structured or unstructured EHR data were developed into an expansible standards-based framework using Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR). METHODS FHIR resources and related properties on indicators were extracted to continuously monitor functional recovery and confirm the treatment effects of integrated care using eastern and western medicine in patients with central nervous system (CNS) injuries. FHIR elements were manually annotated in clinical records generated during patient treatment. RESULTS The results demonstrated the suitability of FHIR-based systems in normalizing both structured and unstructured EHR data. CONCLUSIONS Clinical research plays a vital role in advancing medical knowledge and improving clinical outcomes. CLINICALTRIAL Institutional Review Board (IRB) approval was obtained for access to data on patients who were admitted and treated for more than 3 months in the Department of Rehabilitation for CNS injury between December 2015 and July 2019 (CR-19-115-L).