Leveraging cognitive science and artificial intelligence to save lives

Matthew Jensen Hays, Aaron Richard Glick, H. Chad Lane

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Medical error is the third-leading cause of death in the United States, just behind heart disease and cancer. We describe a software platform used to train healthcare workers to prevent their errors. The platform (Amplifire) harnesses artificial intelligence and principles of cognitive psychology. Amplifire’s AI continuously decides whether and when to require additional learning events, provide corrective and metacognitive feedback, and/or deliver self-regulatory guidance for the learner (e.g., “slow down”). Amplifire was deployed to several thousand nurses at a large healthcare system in attempts to reduce the rate of two types of hospital-acquired infections. The result was a 48% reduction in central-line-associated bloodstream infections (CLABSI) and a 32% reduction in catheter-associated urinary-tract infections (CAUTI). These findings demonstrate the effectiveness of using cognitive science along with AI in an e-learning platform.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 20th International Conference, AIED 2019, Proceedings
EditorsSeiji Isotani, Eva Millán, Amy Ogan, Bruce McLaren, Peter Hastings, Rose Luckin
PublisherSpringer
Pages386-391
Number of pages6
ISBN (Print)9783030232061
DOIs
StatePublished - 2019
Event20th International Conference on Artificial Intelligence in Education, AIED 2019 - Chicago, United States
Duration: Jun 25 2019Jun 29 2019

Publication series

NameLecture Notes in Artificial Intelligence

Conference

Conference20th International Conference on Artificial Intelligence in Education, AIED 2019
Country/TerritoryUnited States
CityChicago
Period6/25/196/29/19

Keywords

  • Artificial intelligence
  • CAUTI
  • CLABSI
  • Cognitive science
  • Confidence
  • Feedback
  • Healthcare
  • Metacognition
  • Training

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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