Maximizing Research on Long COVID using FHIR and OMOP

Authors

  • Eugenia RINALDI Berlin Institute of Health at Charité-Universitaetsmedizin Berlin, Luisenstr. 65 10117 Berlin, Germany
  • Lorenzo CANZIANI University of Verona, Via S. Francesco, 22, Verona, Italy
  • Salvatore CAUTADELLA Cineca Consorzio Interuniversitario, Bologna, Via Magnanelli, 6/3, 40033 Casalecchio di Reno BO, Italy
  • Chiara DELLACASA Cineca Consorzio Interuniversitario, Bologna, Via Magnanelli, 6/3, 40033 Casalecchio di Reno BO, Italy
  • Anna GORSKA University of Verona, Via S. Francesco, 22, Verona, Italy
  • Juan Mata NARANJO Cineca Consorzio Interuniversitario, Bologna, Via Magnanelli, 6/3, 40033 Casalecchio di Reno BO, Italy
  • Thomas OSMO Centre Informatique National de l'Enseignement Supérieur, 950 Rue de St - Priest, 34000 Montpellier, France
  • Miroslav PUSKARIC High-Performance Computing Center, Nobelstraße 19, 70569 Stuttgart, Germany
  • Elisa ROSSI Cineca Consorzio Interuniversitario, Bologna, Via Magnanelli, 6/3, 40033 Casalecchio di Reno BO, Italy
  • Sylvia THUN Berlin Institute of Health at Charité-Universitaetsmedizin Berlin, Luisenstr. 65 10117 Berlin, Germany

Keywords:

FHIR, OMOP CDM, Long COVID, Standard, Interoperability

Abstract

In 2020 The European commission funded the ORCHESTRA project with the aim to join the efforts of several European research centers in the research around the COVID-19 disease. One of the main challenges was to harmonize data across the different cohorts and countries. The introduction of standard terminologies such as SNOMED CT or LOINC helped establish a common language within the project. Over 3500 variables from several information categories were mapped to international codes from standard terminologies. After four years since the start of the pandemic, the study of long COVID seems to be of particular relevance due to the long-term effects that some people keep experiencing even after the infection has disappeared. To facilitate this research, we selected the ORCHESTRA variables that concerned long COVID and mapped them to the standards FHIR and OMOP to possibly support further data exchange with other research organizations.

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Published

21.11.2024

How to Cite

1.
RINALDI E, CANZIANI L, CAUTADELLA S, DELLACASA C, GORSKA A, NARANJO JM, OSMO T, PUSKARIC M, ROSSI E, THUN S. Maximizing Research on Long COVID using FHIR and OMOP. Appl Med Inform [Internet]. 2024 Nov. 21 [cited 2024 Dec. 3];46(Suppl. 2):S25-S28. Available from: https://ami.info.umfcluj.ro/index.php/AMI/article/view/1078