Environmental and clinical data utility in pediatric asthma exacerbation risk prediction models.

Journal: BMC medical informatics and decision making
Published Date: Apr 22, 2022

Abstract

BACKGROUND: Asthma exacerbations are triggered by a variety of clinical and environmental factors, but their relative impacts on exacerbation risk are unclear. There is a critical need to develop methods to identify children at high-risk for future exacerbation to allow targeted prevention measures. We sought to evaluate the utility of models using spatiotemporally resolved climatic data and individual electronic health records (EHR) in predicting pediatric asthma exacerbations.

Authors

  • Jillian H Hurst
    Department of Pediatrics, Division of Infectious Diseases, Duke University School of Medicine, Durham, NC, USA.
  • Congwen Zhao
    Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, NC, USA.
  • Haley P Hostetler
    Department of Medicine, Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University School of Medicine, Durham, NC, USA.
  • Mohsen Ghiasi Gorveh
    Duke Clinical Research Institute, Duke University, Durham, NC, USA.
  • Jason E Lang
    Department of Pediatrics, Division of Pulmonary and Sleep Medicine, Duke University School of Medicine, Durham, NC, USA.
  • Benjamin A Goldstein
    Department of Biostatistics and Bioinformatics, Duke University School of Medicine, Durham, North Carolina.

Keywords

External Resources

Popular Topics
Recent Journals