Data standardization implementation and applications within and among diagnostic laboratories: integrating and monitoring enteric coronaviruses

Giovani Trevisan, Leticia C.M. Linhares, Kent J. Schwartz, Eric R. Burrough, Edison de S. Magalhães, Bret Crim, Poonam Dubey, Rodger G. Main, Phillip Gauger, Mary Thurn, Paulo T.F. Lages, Cesar A. Corzo, Jerry Torrison, Jamie Henningson, Eric Herrman, Rob McGaughey, Giselle Cino, Jon Greseth, Travis Clement, Jane Christopher-HenningsDaniel C.L. Linhares

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Every day, thousands of samples from diverse populations of animals are submitted to veterinary diagnostic laboratories (VDLs) for testing. Each VDL has its own laboratory information management system (LIMS), with processes and procedures to capture submission information, perform laboratory tests, define the boundaries of test results (i.e., positive or negative), and report results, in addition to internal business and accounting applications. Enormous quantities of data are accumulated and stored within VDL LIMSs. There is a need for platforms that allow VDLs to exchange and share portions of laboratory data using standardized, reliable, and sustainable information technology processes. Here we report concepts and applications for standardization and aggregation of data from swine submissions to multiple VDLs to detect and monitor porcine enteric coronaviruses by RT-PCR. Oral fluids, feces, and fecal swabs were the specimens submitted most frequently for enteric coronavirus testing. Statistical algorithms were used successfully to scan and monitor the overall and state-specific percentage of positive submissions. Major findings revealed a consistently recurrent seasonal pattern, with the highest percentage of positive submissions detected during December–February for porcine epidemic diarrhea virus, porcine deltacoronavirus, and transmissible gastroenteritis virus (TGEV). After 2014, very few submissions tested positive for TGEV. Monitoring VDL data proactively has the potential to signal and alert stakeholders early of significant changes from expected detection. We demonstrate the importance of, and applications for, data organized and aggregated by using LOINC and SNOMED CTs, as well as the use of customized messaging to allow inter-VDL exchange of information.

Original languageEnglish (US)
Pages (from-to)457-468
Number of pages12
JournalJournal of Veterinary Diagnostic Investigation
Issue number3
StatePublished - May 2021

Bibliographical note

Funding Information:
We thank VDL clients for submitting samples for testing. We also thank current and former SDRS advisory group members for their valuable input and volunteered time: Drs. Clayton Johnson, Emily Byers, Hans Rotto, Jeremy Pittman, Mark Schwartz, Paul Yeske, Pete Thomas, Rebecca Robbins, Tara Donovan, Matthew Turner, Deborah Murray, Scott Dee, Melissa Hensch, Scanlon Daniels, Brigitte Mason, and Randy Jones. This project was co-funded by the American Association of Swine Veterinarians Foundation award 018743-00001, by the Swine Health Information Center (SHIC) awards 17-210 and 19-155 SHIC, and by the USDA National Institute of Food and Agriculture Animal Health and Disease Research Capacity Funds project 1017372 to D.C.L. Linhares.

Publisher Copyright:
© 2021 The Author(s).


  • PDCoV
  • PEDV
  • TGEV
  • data integration
  • data standardization
  • enteric coronavirus
  • monitoring
  • veterinary diagnostic laboratories

PubMed: MeSH publication types

  • Journal Article


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