Electronic Health Record (EHR) Work Group
Limits in the type and quality of pain-relevant data in Electronic Health Records (EHRs) is a critical barrier to the conduct of pragmatic clinical trials of non-pharmacological approaches to pain management in the VA and DoD health systems—or, actually, in virtually all practice settings. The EHR Work Group aims to optimize the use of existing electronic health data, integrate patient reported data, and extract new data from unstructured text using innovative techniques, including machine learning and natural language processing. Working across two health systems (VHA and DHA), the work group will promote harmonization and interoperability to develop tools and adopt solutions to support the pragmatic trials.
Chair or Co-Chairs:
Joseph Erdos, MD, PhD
Michael Matheny, MD, MS, MPH
Work Group Goals
Work Group Co-Chairs – Qualifications and Experience
Joseph Erdos, MD, PhD, was the VACHS Chief Information Officer from 1995 to 2011 and was a member of the VA Chief Information Officers Council. He was instrumental in the early design and implementation of the VistA EHR system into care in 1999 as well as VistA Imaging. A demonstration project on Telemedicine at VA Connecticut led to the development of home telemedicine in the VA. In 2011 Dr. Erdos was tasked with development of the VA’s Corporate Data Warehouse (CDW), a repository of standardized mapped, accessible, EHR data for operations and research. He was promoted to serve as Director of the VA East Coast Business Intelligence Service Line of the Office of Information. He and his co-directors have overseen the conception and implementation of the VA CDW which has extracted and modeled over 50 clinical and administrative domains from approximately 150 VistA platforms resulting in approximately 2 trillion rows of data! Dr. Erdos has experience in VistA, Cerner, Epic, CHCS, AHLTA and other EHRs and systems used over the years. He daily advises PRIME investigators in the appropriate use of VA data to achieve their goals. If data do not exist in the CDW he provides tools and develops methods to get them.
Michael Matheny, M.S., M.D. is an Associate Professor of Biomedical Informatics with secondary appointments in Medicine and Biostatistics at Vanderbilt University Medical Center. He is a board certified in Internal Medicine and Clinical Informatics. Dr. Matheny is a nationally recognized investigator in predictive analytics, machine learning, automated medical device surveillance, and NLP. His work focuses on studying how to best leverage large EHR data for discovery of risk prediction using both structured data and NLP derived data, as well as conducting automated adverse event surveillance in medical devices. He is an Associate Director of VA HSR&D VINCI which helps provision data to the VA research community and provide informatics and health services research tools to assist in studies. He is also deeply involved with the Joint Interagency Funded initiative to provide DoD data for those patients registered in the VA and helping lead the initiative to transform both the VA and DoD data sources into the Observational Medical Outcomes Partnership (OMOP) common data model. He is the Co-PI of the pScanner PCORI Clinical Data Research Network and is the lead investigator for the VA for this initiative that executes an array of distributed analytic queries for large-scale observational cohort analyses.