Please read Dr. Geller’s from the 2020 IEEE International Conference on Big Data (Big Data) titled, “Mining Concepts for a COVID Interface Terminology for Annotation of EHRs.”
COVID-19 has turned into the greatest healthcare challenge since the Spanish flu pandemic, causing millions of infections and over one million deaths. Meanwhile, the Electronic Health Records (EHRs) in hospitals are ingesting a deluge of COVID-19 cases and morbidity information. COVID-19 uncovered weaknesses in US health information management practices that hamper research on the disease. At the early stages of this pandemic, doctors have been describing signs and symptoms in various organ systems, e.g., “COVID toes” and Multisystem Inflammatory Syndrome in Children (MIS-C). However, most of these terms are not coded and are only recorded as free text, inhibiting interoperability, and the use of EHR notes for research on the disease. How can we support research on “COVID toes” and other related COVID-19 rashes (for example), if we cannot code such findings in the EHR to make them easily discoverable, and doctors and clinical software are forced to search for them as free text instead of as concepts? To read the full article.
Mining Concepts for a COVID Interface Terminology for Annotation of EHRs. Keloth VK, Zhou SX, Lindemann L, Elhanan G, Einstein AJ, Geller J, Perl Y. IEEE International Conference on Big Data (Big Data), pp. 3753-3760. DOI: 10.1109/BigData50022.2020.9377981.