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Data standardization implementation and applications within and among diagnostic laboratories: integrating and monitoring enteric coronaviruses.
Trevisan, Giovani; Linhares, Leticia C M; Schwartz, Kent J; Burrough, Eric R; Magalhães, Edison de S; Crim, Bret; Dubey, Poonam; Main, Rodger G; Gauger, Phillip; Thurn, Mary; Lages, Paulo T F; Corzo, Cesar A; Torrison, Jerry; Henningson, Jamie; Herrman, Eric; McGaughey, Rob; Cino, Giselle; Greseth, Jon; Clement, Travis; Christopher-Hennings, Jane; Linhares, Daniel C L.
Afiliação
  • Trevisan G; Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
  • Linhares LCM; Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
  • Schwartz KJ; Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
  • Burrough ER; Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
  • Magalhães ES; Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
  • Crim B; Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
  • Dubey P; Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
  • Main RG; Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
  • Gauger P; Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
  • Thurn M; Veterinary Population Medicine, University of Minnesota, Saint Paul, MN.
  • Lages PTF; Veterinary Population Medicine, University of Minnesota, Saint Paul, MN.
  • Corzo CA; Veterinary Population Medicine, University of Minnesota, Saint Paul, MN.
  • Torrison J; Veterinary Population Medicine, University of Minnesota, Saint Paul, MN.
  • Henningson J; College of Veterinary Medicine, Kansas State University, Manhattan, KS.
  • Herrman E; College of Veterinary Medicine, Kansas State University, Manhattan, KS.
  • McGaughey R; College of Veterinary Medicine, Kansas State University, Manhattan, KS.
  • Cino G; College of Veterinary Medicine, Kansas State University, Manhattan, KS.
  • Greseth J; Veterinary & Biomedical Sciences Department, South Dakota State University, Brookings, SD.
  • Clement T; Veterinary & Biomedical Sciences Department, South Dakota State University, Brookings, SD.
  • Christopher-Hennings J; Veterinary & Biomedical Sciences Department, South Dakota State University, Brookings, SD.
  • Linhares DCL; Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA.
J Vet Diagn Invest ; 33(3): 457-468, 2021 May.
Article em En | MEDLINE | ID: mdl-33739188
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doenças dos Suínos / Coronaviridae / Infecções por Coronaviridae / Laboratórios Tipo de estudo: Diagnostic_studies Limite: Animals Idioma: En Revista: J Vet Diagn Invest Assunto da revista: MEDICINA VETERINARIA Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Doenças dos Suínos / Coronaviridae / Infecções por Coronaviridae / Laboratórios Tipo de estudo: Diagnostic_studies Limite: Animals Idioma: En Revista: J Vet Diagn Invest Assunto da revista: MEDICINA VETERINARIA Ano de publicação: 2021 Tipo de documento: Article