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Making electronic prescribing alerts more effective: scenario-based experimental study in junior doctors
Gregory P T Scott1, Priya Shah, Jeremy C Wyatt
1Department of Health Informatics Directorate, Leeds, West Yorkshire, UK. gregory.scott99@imperial.ac.uk
Journal of the American Medical Informatics Association : JAMIA
|August 13, 2011
Summary
Modal electronic prescribing alerts significantly reduce medication errors more than non-modal alerts. This study compared alert types to improve clinical decision support systems and reduce prescribing errors.
Area of Science:
- Medical Informatics
- Clinical Pharmacy
- Human-Computer Interaction
Background:
- Clinical decision support systems aim to reduce prescribing errors but often use disruptive modal alerts.
- Modal alerts can interrupt clinicians, potentially limiting the effectiveness of electronic prescribing (e-prescribing) systems.
Purpose of the Study:
- To compare the impact of modal and non-modal e-prescribing alerts on prescribing error rates.
- To inform the design of more effective clinical decision support systems.
Main Methods:
- A randomized controlled trial involving 24 junior doctors performing simulated prescribing tasks.
- Participants were exposed to modal alerts, non-modal alerts, or no alerts during tasks using a within-participant design.
Main Results:
- Modal alerts were associated with an 11.6-fold reduction in prescribing errors compared to no alerts.
- Non-modal alerts reduced errors 3.2-fold compared to no alerts.
- Modal alerts were over three times more effective than non-modal alerts in reducing errors.
Conclusions:
- Both modal and non-modal e-prescribing alerts significantly decrease prescribing error rates.
- Modal alerts demonstrate superior effectiveness in reducing prescribing errors compared to non-modal alerts.
- Findings provide evidence for optimizing alert design in clinical decision support systems.
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