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Using Electronic Medical Records to Identify Enhanced Recovery After Surgery Cases.

Nikki L B FreemanKatharine L McGiniglePeter J Leese
Published in: EGEMS (Washington, DC) (2019)
ERAS pathways are complex, making study of them from EMRs difficult. Current strategies for doing so are relatively easy to implement, but unreliable. We have developed a reproducible and observable ERAS computational phenotype that identifies ERAS cases reliably. This is a step forward in using the richness of EMR data to study ERAS implementation, efficacy, and how they can contribute to surgical care improvement.
Keyphrases
  • healthcare
  • primary care
  • quality improvement
  • machine learning
  • gene expression
  • dna methylation
  • deep learning