Assessing Disparities in COVID-19 Testing Using National COVID Cohort Collaborative

Jinyan Lyu, Wanting Cui, Joseph Finkelstein

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

With NCATS National COVID Cohort Collaborative (N3C) dataset, we evaluated 14 billion medical records and identified more than 12 million patients tested for COVID-19 across the US. To assess potential disparities in COVID-19 testing, we chose ten US states and then compared each state's population distribution characteristics with distribution of corresponding characteristics from N3C. Minority racial groups were more prevalent in the N3C dataset as compared to census data. The proportion of Hispanics and Latinos in N3C was slightly lower than in the state census. Patients over 65 years old had higher representation in the N3C dataset and patients under 18 were underrepresented. Proportion of females in the N3C was higher compared with the state data. All ten states in N3C showed a higher representation of urban population versus rural population compared to census data.

Original languageEnglish
Title of host publicationAdvances in Informatics, Management and Technology in Healthcare
EditorsJohn Mantas, Parisis Gallos, Emmanouil Zoulias, Arie Hasman, Mowafa S. Househ, Marianna Diomidous, Joseph Liaskos, Martha Charalampidou
PublisherIOS Press BV
Pages316-319
Number of pages4
ISBN (Electronic)9781643682907
DOIs
StatePublished - 2022

Publication series

NameStudies in Health Technology and Informatics
Volume295
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Keywords

  • COVID-19
  • data integrity
  • national COVID cohort collaborative

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