Meet The Speaker
“Bright ideas lurking in clinical data: Finding the meaning in medical records for research and quality”
Andrew Post, MD, PhD is Assistant Professor in Emory University’s Department of Biomedical Informatics and Clinical Informatics Architect in Emory’s Center for Comprehensive Informatics. Dr. Post received his MD from the University of Pennsylvania and his PhD in Biomedical Informatics from the University of Pittsburgh. In his role as Clinical Informatics Architect, Dr. Post leads clinical data warehouse-related projects at Emory Healthcare. He also leads a software development team in translating novel clinical research informatics methods into production-quality software for deployment at Emory and beyond. In his role in the Department of Biomedical Informatics, he conducts research in temporal query, extract, transform and load processes and healthcare analytics involving clinical data. Dr. Post is Interim Director of the Atlanta Clinical and Translational Science Institute’s Biomedical Informatics Program, where he leads efforts to create coordinated access to and management of clinical data across multiple clinical sites in the Atlanta area.
Seminar Abstract
“Bright ideas lurking in clinical data: finding the meaning in medical records for research and quality”
Clinical data warehouses represent a history of patient care at an institution. They contain data from EHRs and billing systems, and they store computed values and metrics that represent aspects of patient care at the population level. While data warehouses are becoming commonplace at large health systems, the tools for getting data out of them in meaningful form require substantial technical background and expertise. Requiring a technical intermediary even for simple data requests does not scale and limits the utility of a data warehouse. It’s not just the quantity of data that prevents direct use by clinicians, administrators and scientists. Data complexity, and using data for population analyses that were not collected for that purpose, are even greater challenges. I will present a software tool that we are developing, called Eureka! Clinical Analytics, that aims to manage this complexity and data volume to enable non-technical users to interact with and extract meaning reliably from electronic health record data. I will show how its architecture and implementation support those goals in quality improvement and research.
