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Towards The Automated, Empirical Filtering of Drug-Drug Interaction Alerts in Clinical Decision Support Systems: Historical Cohort Study of Vitamin K Antagonists.

Emmanuel ChazardAugustin BoudryPatrick Emanuel BeelerOlivia DalleurHervé HubertEric TréhouJean-Baptiste BeuscartDavid Westfall Bates
Published in: JMIR medical informatics (2021)
The probabilities of outcomes obtained were not those expected on the basis of our current body of pharmacological knowledge. The results do not cast doubt on our current pharmacological knowledge per se but do challenge the commonly accepted idea whereby this knowledge alone should be used to define when a DDI alert should be displayed. Real-life probabilities should also be considered during the filtration of DDI alerts by CDSSs, as proposed in SPC-CDSS (statistically prioritized and contextualized CDSS). However, these probabilities may differ from one hospital to another and so should probably be calculated locally.
Keyphrases
  • clinical decision support
  • healthcare
  • electronic health record
  • adverse drug
  • machine learning
  • metabolic syndrome
  • type diabetes
  • skeletal muscle
  • drug induced
  • insulin resistance
  • glycemic control