Repurposing Clinical Decision Support System Data to Measure Dosing Errors and Clinician-Level Quality of Care

David L. Chin, Michelle H. Wilson, Ashley S. Trask, Victoria T. Johnson, Brittanie I. Neaves, Andrea Gojova, Michael A Hogarth, Heejung Bang, Patrick S Romano

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


We aimed to develop and validate an instrument to detect hospital medication prescribing errors using repurposed clinical decision support system data. Despite significant efforts to eliminate medication prescribing errors, these events remain common in hospitals. Data from clinical decision support systems have not been used to identify prescribing errors as an instrument for physician-level performance. We evaluated medication order alerts generated by a knowledge-based electronic prescribing system occurring in one large academic medical center’s acute care facilities for patient encounters between 2009 and 2012. We developed and validated an instrument to detect medication prescribing errors through a clinical expert panel consensus process to assess physician quality of care. Six medication prescribing alert categories were evaluated for inclusion, one of which – dose – was included in the algorithm to detect prescribing errors. The instrument was 93% sensitive (recall), 51% specific, 40% precise, 62% accurate, with an F1 score of 55%, positive predictive value of 96%, and a negative predictive value of 32%. Using repurposed electronic prescribing system data, dose alert overrides can be used to systematically detect medication prescribing errors occurring in an inpatient setting with high sensitivity.

Original languageEnglish (US)
Article number185
JournalJournal of medical systems
Issue number10
StatePublished - Oct 1 2020


  • Decision support systems, clinical
  • Electronic health records
  • Medical informatics applications
  • Medication errors
  • Outcome and process assessment (health care)
  • Quality of health care

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Information Systems
  • Health Informatics
  • Health Information Management


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