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Trend of incompleteness of the race/color variable in hospitalizations due to COVID-19 whose outcome was death in Brazil, 2020-2022.

Hebert Luan Pereira Campos Dos SantosEmmanuel Santos TrindadeEsly Rebeca Amaral OliveiraMarcos Vinicius da Silva CordeiroRian Silva de OliveiraElvira Caires de LimaAdriano Maia Dos SantosNilia Maria de Brito Lima Prado
Published in: Revista de saude publica (2024)
The proportion of poor completeness and the stable trend of incompleteness show that there was no improvement in the quality of filling in the race/color variable during the COVID-19 pandemic in Brazil, a fact that may have increased health inequalities for the black population and made it difficult to plan strategic actions for this population, considering the pandemic context. The results found reinforce the need to encourage discussion on the subject, given that the incompleteness of health information systems increases inequalities in access to health services and compromises the quality of health data.
Keyphrases
  • machine learning
  • health information
  • big data
  • coronavirus disease
  • sars cov
  • social media
  • healthcare
  • public health
  • mental health
  • quality improvement
  • risk assessment
  • health promotion