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COVID-19 TestNorm: A tool to normalize COVID-19 testing names to LOINC codes.
Dong, Xiao; Li, Jianfu; Soysal, Ekin; Bian, Jiang; DuVall, Scott L; Hanchrow, Elizabeth; Liu, Hongfang; Lynch, Kristine E; Matheny, Michael; Natarajan, Karthik; Ohno-Machado, Lucila; Pakhomov, Serguei; Reeves, Ruth Madeleine; Sitapati, Amy M; Abhyankar, Swapna; Cullen, Theresa; Deckard, Jami; Jiang, Xiaoqian; Murphy, Robert; Xu, Hua.
  • Dong X; School of Biomedical Informatics, University of Texas, Houston, Texas, USA.
  • Li J; School of Biomedical Informatics, University of Texas, Houston, Texas, USA.
  • Soysal E; School of Biomedical Informatics, University of Texas, Houston, Texas, USA.
  • Bian J; Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, Florida, USA.
  • DuVall SL; VA Informatics and Computing Infrastructure, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, Utah, USA.
  • Hanchrow E; Department of Internal Medicine Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah, USA.
  • Liu H; Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, Tennessee, USA.
  • Lynch KE; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
  • Matheny M; Division of Digital Health Sciences, Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA.
  • Natarajan K; VA Informatics and Computing Infrastructure, Veterans Affairs Salt Lake City Health Care System, Salt Lake City, Utah, USA.
  • Ohno-Machado L; Department of Internal Medicine Division of Epidemiology, University of Utah School of Medicine, Salt Lake City, Utah, USA.
  • Pakhomov S; Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, Tennessee, USA.
  • Reeves RM; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
  • Sitapati AM; Department of Biomedical Informatics, Columbia University Irving Medical Center, New York, New York, USA.
  • Abhyankar S; Medical Informatics Services, NewYork-Presbyterian Hospital, New York, New York, USA.
  • Cullen T; Department of Biomedical Informatics, UCSD Health, University of California, San Diego, La Jolla, California, USA.
  • Deckard J; Division of Health Services Research and Development, Veterans Administration San Diego Healthcare System, La Jolla, California, USA.
  • Jiang X; Department of Pharmaceutical Care and Health Systems, College of Pharmacy, University of Minnesota, Minneapolis, Minnesota, USA.
  • Murphy R; Tennessee Valley Healthcare System, Veterans Affairs Medical Center, Nashville, Tennessee, USA.
  • Xu H; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
J Am Med Inform Assoc ; 27(9): 1437-1442, 2020 07 01.
Article in English | MEDLINE | ID: covidwho-610367
ABSTRACT
Large observational data networks that leverage routine clinical practice data in electronic health records (EHRs) are critical resources for research on coronavirus disease 2019 (COVID-19). Data normalization is a key challenge for the secondary use of EHRs for COVID-19 research across institutions. In this study, we addressed the challenge of automating the normalization of COVID-19 diagnostic tests, which are critical data elements, but for which controlled terminology terms were published after clinical implementation. We developed a simple but effective rule-based tool called COVID-19 TestNorm to automatically normalize local COVID-19 testing names to standard LOINC (Logical Observation Identifiers Names and Codes) codes. COVID-19 TestNorm was developed and evaluated using 568 test names collected from 8 healthcare systems. Our results show that it could achieve an accuracy of 97.4% on an independent test set. COVID-19 TestNorm is available as an open-source package for developers and as an online Web application for end users (https//clamp.uth.edu/covid/loinc.php). We believe that it will be a useful tool to support secondary use of EHRs for research on COVID-19.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Clinical Laboratory Techniques / Logical Observation Identifiers Names and Codes / Betacoronavirus / Terminology as Topic Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: J Am Med Inform Assoc Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: Jamia

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pneumonia, Viral / Coronavirus Infections / Clinical Laboratory Techniques / Logical Observation Identifiers Names and Codes / Betacoronavirus / Terminology as Topic Type of study: Diagnostic study / Experimental Studies / Observational study / Prognostic study Limits: Humans Language: English Journal: J Am Med Inform Assoc Journal subject: Medical Informatics Year: 2020 Document Type: Article Affiliation country: Jamia