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Implementation approaches and barriers for rule-based and machine learning-based sepsis risk prediction tools: a qualitative study.

Mugdha JoshiKeizra MecklaiRonen RozenblumLipika Samal
Published in: JAMIA open (2022)
Further implementation science research is needed to determine real world efficacy of these tools. Clinician acceptance is a significant barrier to sepsis CDS implementation. Successful implementation of less clinically intuitive ML models may require additional attention to user confusion and distrust.
Keyphrases
  • primary care
  • healthcare
  • quality improvement
  • machine learning
  • intensive care unit
  • acute kidney injury
  • septic shock
  • public health
  • working memory
  • artificial intelligence