Algorithmic Detection of Boolean Logic Errors in Clinical Decision Support StatementsFunding Research reported in this publication was supported by the National Library of Medicine of the National Institutes of Health under Award Number R01LM011966. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Objective Clinical decision support (CDS) can contribute to quality and safety. Prior work has shown that errors in CDS systems are common and can lead to unintended consequences. Many CDS systems use Boolean logic, which can be difficult for CDS analysts to specify accurately. We set out to determine the prevalence of certain types of Boolean logic errors in CDS statements.
Methods Nine health care organizations extracted Boolean logic statements from their Epic electronic health record (EHR). We developed an open-source software tool, which implemented the Espresso logic minimization algorithm, to identify three classes of logic errors.
Results Participating organizations submitted 260,698 logic statements, of which 44,890 were minimized by Espresso. We found errors in 209 of them. Every participating organization had at least two errors, and all organizations reported that they would act on the feedback.
Discussion An automated algorithm can readily detect specific categories of Boolean CDS logic errors. These errors represent a minority of CDS errors, but very likely require correction to avoid patient safety issues. This process found only a few errors at each site, but the problem appears to be widespread, affecting all participating organizations.
Conclusion Both CDS implementers and EHR vendors should consider implementing similar algorithms as part of the CDS authoring process to reduce the number of errors in their CDS interventions.
Keywordsclinical decision support - electronic health records and systems - alerting - decision support algorithm - efficiency improvement
Protection of Human and Animal Subjects
Human and/or animal subjects were not included in this project.
A.W. wrote the manuscript and conceived the study design. S.A. wrote the logic minimization program. D.F. acted as a tester for the logic minimization program. All authors provided data. All authors provided critical revisions for important intellectual content.
Received: 11 August 2020
Accepted: 16 December 2020
10 March 2021 (online)
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