Evidence-based decision support for neurological diagnosis reduces errors and unnecessary workup

Michael M. Segal, Marc S. Williams, Andrea L. Gropman, Alcy R. Torres, Rob Forsyth, Anne M. Connolly, Ayman W. El-Hattab, Seth J. Perlman, Debopam Samanta, Sumit Parikh, Steven G. Pavlakis, Lynn K. Feldman, Rebecca A. Betensky, Sidney M. Gospe

Research output: Contribution to journalArticlepeer-review

22 Scopus citations

Abstract

Using vignettes of real cases and the SimulConsult diagnostic decision support software, neurologists listed a differential diagnosis and workup before and after using the decision support. Using the software, there was a significant reduction in error, up to 75% for diagnosis and 56% for workup. This error reduction occurred despite the baseline being one in which testers were allowed to use narrative resources and Web searching. A key factor that improved performance was taking enough time (>2 minutes) to enter clinical findings into the software accurately. Under these conditions and for instances in which the diagnoses changed based on using the software, diagnostic accuracy improved in 96% of instances. There was a 6% decrease in the number of workup items accompanied by a 34% increase in relevance. The authors conclude that decision support for a neurological diagnosis can reduce errors and save on unnecessary testing.

Original languageEnglish
Pages (from-to)487-492
Number of pages6
JournalJournal of Child Neurology
Volume29
Issue number4
DOIs
StatePublished - Apr 2014

Keywords

  • decision support
  • diagnosis
  • errors
  • genetics
  • medical informatics
  • neurogenetics

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