Doctor of Philosophy (PhD)
The University of Texas School of Biomedical Informatics at Houston
Sahiti Myneni, PhD
Advances in efficiency while maintaining or improving quality are immediately needed in clinical research, specifically for multicenter clinical studies. Though recent evidence points toward electronic health record (EHR) to electronic data capture (EDC) system (EHR to EDC) data collection as a viable contribution, there are many unanswered process and outcome-level questions regarding quality, site burden, and cost within the context of multicenter clinical trials. Direct extraction and use of EHR data in multicenter clinical studies is a long-term and multifaceted endeavor that includes design, development, implementation and evaluation of methods and tools for semi-automating tasks in the research data collection process, such as medical record abstraction (MRA). Both industry and federal agencies have continued to encourage the development and advancement of solutions that promote optimal usage of electronic data sources in clinical research (FDA, 2013; Kellar, et al., 2016). In 2013, the Food and Drug Administration (FDA) issued a guidance for use of electronic source (eSource) data in clinical investigations (FDA, 2013) – the term ‘eSource’ is often used colloquially to refer to the method of direct capture, collection, and storage of electronic source data (e.g., EHR data) in an effort to streamline clinical research. Although several federal guidelines and industry standards exist, the development, implementation, and evaluation of eSource solutions has been limited (Garza, et al., 2019) and manual “transcription between electronic systems continues to be the norm” (Kellar, et al., 2016).
The work conducted for this dissertation is only a small fraction of a much larger collaborative effort that aims to design, develop, implement, and evaluate a standards-based, EHR and EDC-agnostic, open-source eSource solution for multicenter clinical research studies. Here, the scope is limited to the evaluation of the data coverage and utility of the Health Level Seven (HL7®) Fast Healthcare Interoperability Resources (FHIR®) standard in supporting EHR and EDC-agnostic eSource implementations. This research, conducted within the context of an existing multicenter clinical research study for which formalized MRA training and ongoing quality control reviews were performed, expands upon the work of previous pivotal studies to address the gaps identified in the existing literature, specifically targeting generalizability and scalability. The results of this effort can be used to inform ongoing and future eSource implementation projects and development efforts by providing evidence to support the use of the HL7® FHIR® standard for the direct extraction of EHR data in clinical research. The outcomes assessed here have not been previously achieved in the context of a multicenter clinical study and demonstrate the potential improvements in data quality and collection.
Garza, Maryam, "Determining the Utility of HL7® Fast Healthcare Interoperability Resources (FHIR®) Standards in Supporting EHR and EDC-agnostic eSource Implementations for Clinical Research" (2020). Dissertations (Open Access). 50.
Electronic health record (EHR), electronic data capture (EDC), medical record abstraction, semi-structured interviews