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In the case of systematic errors, the sources can be identified, and the errors can be subsequently minimized by addressing these sources. According to the source, systematic errors can be divided into sampling, instrumental, methodological, and personal errors.
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Random or indeterminate errors originate from various uncontrollable variables, such as variations in environmental conditions, instrument imperfections, or the inherent variability of the phenomena being measured. Usually, these errors cannot be predicted, estimated, or characterized because their direction and magnitude often vary in magnitude and direction even during consecutive measurements. As a result, they are difficult to eliminate. However, the aggregate effect of these errors can be...
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Reduced Verification of Medication Alerts Increases Prescribing Errors.

David Lyell1, Farah Magrabi1, Enrico Coiera1

  • 1Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, New South Wales, Australia.

Applied Clinical Informatics
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Clinicians may over-rely on clinical decision support (CDS) systems, leading to reduced verification of medication prescriptions. This reduced verification, especially with incorrect CDS alerts, is linked to an increase in prescribing errors.

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Area of Science:

  • Medical Informatics
  • Patient Safety
  • Human Factors Engineering

Background:

  • Clinicians must ensure prescription safety, often using drug references for verification.
  • Overreliance on decision support in other fields is linked to errors due to reduced verification.
  • The impact of clinical decision support (CDS) on verification behaviors and prescribing errors in medicine is not well understood.

Purpose of the Study:

  • To investigate the relationship between verification behaviors and prescribing errors.
  • To determine if this relationship is influenced by the presence and accuracy of CDS medication alerts.
  • To examine the mediating role of task complexity in this relationship.

Main Methods:

  • 120 medical students used a simulated electronic prescribing system.
  • Prescribing tasks involved varying levels of CDS (correct, incorrect, none) and task complexity (low, high).
  • Outcomes measured were omission and commission errors, with verification assessed by drug reference access and view time.

Main Results:

  • Failure to access drug references increased omission and commission errors, particularly with incorrect CDS.
  • Fewer references were accessed with incorrect CDS compared to no CDS.
  • Lower reference view time percentages correlated with increased omission and commission errors.
  • CDS use, regardless of accuracy, was associated with reduced verification time.

Conclusions:

  • Clinical decision support (CDS) can reduce prescription safety verification.
  • When CDS provides incorrect alerts, reduced verification is associated with more prescribing errors.
  • System design should support verification without compromising CDS benefits or increasing workload.