49.5 AMA PRA Category 1 Credit(s)™ available
Data Standards for Learning Health Systems
This course will explore the concept of learning health systems and closely examine the specific data standards required to support the data exchange and re-use in this context. Learners will appreciate the heterogeneity and complexity of existing standards and identify opportunities to use them in organizational and research activities, including observational studies, pragmatic trials and quality improvement projects. Active and relevant Standards Development Organizations and processes for developing and defining standards will be discussed. Specific topics covered will include tools related to the planning phases for health information systems, as well as standards that support interoperability, including information models, terminology and coding systems, data transport syntax, and structured documents. The development, functionality, uptake, and usability of standards from both national and international perspectives are discussed, along with models for continuous use of clinical data for quality improvement and research. Students will have an opportunity to define a clinical question and the various standards that can support the application and evaluation of evidence in a health care setting.
Suggested pre-requisites include an introductory informatics course and training and/or experience in a health care discipline or clinical research.
Dr. Rachel Richesson is a trained informaticist and joined Duke University in December 2011. She earned her BS (Biology) at the University of Massachusetts in 1991, and holds graduate degrees in Community Health (MPH, 1995) and Biomedical Informatics (MS, 2000 and PhD, 2003) from the University of Texas Health Science Center in Houston. Since 2003, Dr. Richesson has helped to direct strategy for the identification and implementation of data standards for a variety of multi-national multi-site clinical research and epidemiological studies. Dr. Richesson has conducted original research on the quality and usability of various terminological data standards, particularly in the context of clinical research, and has presented dozens of posters and invited talks on the topic of data standards in clinical research. She was inducted as a fellow of the American College of Medical Informatics in 2014.
Dr. Richesson currently chairs the Phenotype, Data Standards, and Data Quality Core for the NIH Health Care Systems Research Collaboratory (https://www.nihcollaboratory.org/Pages/default.aspx) which is developing standardized approaches and quality metrics for using data from electronic health records in pragmatic clinical trials. As part of the Coordinating Center team for The National Patient-Centered Clinical Research Network (PCORnet; http://www.pcori.org/content/pcornet-national-patient-centered-clinical-...) she co-leads the PCORnet Rare Diseases Task Force, supporting standardized approaches to for identifying rare disease patients from EHR systems. Most recently, she edited a JAMIA special issue on the topic of data standards with Dr. Christopher Chute.