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Predicting 30-day return hospital admissions in patients with COVID-19 discharged from the emergency department: A national retrospective cohort study.

David G BeiserZachary J JarouAlaa A KassirMichael A PuskarichMarie C VrablikElizabeth D RosenmanSamuel A McDonaldAndrew C MeltzerD Mark CourtneyChristopher KabrhelJeffrey A Klinenull null
Published in: Journal of the American College of Emergency Physicians open (2021)
A predictive model identifying adult ED patients with COVID-19 at risk for return for return hospital admission within 30 days is feasible. Ensemble/boot-strapped classification methods (eg, GBM, RF, and LASSO) outperform the single-tree CART method. Future efforts may focus on the application of ML models in the hospital setting to optimize the allocation of follow-up resources.
Keyphrases
  • emergency department
  • adverse drug
  • quality improvement
  • healthcare
  • acute care
  • machine learning
  • deep learning
  • current status
  • convolutional neural network
  • young adults
  • electronic health record
  • drug induced