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- Title
Automation bias in electronic prescribing.
- Authors
Lyell, David; Magrabi, Farah; Raban, Magdalena Z.; Pont, L. G.; Baysari, Melissa T.; Day, Richard O.; Coiera, Enrico
- Abstract
<bold>Background: </bold>Clinical decision support (CDS) in e-prescribing can improve safety by alerting potential errors, but introduces new sources of risk. Automation bias (AB) occurs when users over-rely on CDS, reducing vigilance in information seeking and processing. Evidence of AB has been found in other clinical tasks, but has not yet been tested with e-prescribing. This study tests for the presence of AB in e-prescribing and the impact of task complexity and interruptions on AB.<bold>Methods: </bold>One hundred and twenty students in the final two years of a medical degree prescribed medicines for nine clinical scenarios using a simulated e-prescribing system. Quality of CDS (correct, incorrect and no CDS) and task complexity (low, low + interruption and high) were varied between conditions. Omission errors (failure to detect prescribing errors) and commission errors (acceptance of false positive alerts) were measured.<bold>Results: </bold>Compared to scenarios with no CDS, correct CDS reduced omission errors by 38.3% (p < .0001, n = 120), 46.6% (p < .0001, n = 70), and 39.2% (p < .0001, n = 120) for low, low + interrupt and high complexity scenarios respectively. Incorrect CDS increased omission errors by 33.3% (p < .0001, n = 120), 24.5% (p < .009, n = 82), and 26.7% (p < .0001, n = 120). Participants made commission errors, 65.8% (p < .0001, n = 120), 53.5% (p < .0001, n = 82), and 51.7% (p < .0001, n = 120). Task complexity and interruptions had no impact on AB.<bold>Conclusions: </bold>This study found evidence of AB omission and commission errors in e-prescribing. Verification of CDS alerts is key to avoiding AB errors. However, interventions focused on this have had limited success to date. Clinicians should remain vigilant to the risks of CDS failures and verify CDS.
- Subjects
DIGITAL resources on prescription drugs; DECISION support systems -- Medical applications; MEDICAL prescriptions; COMPUTERS in medicine; MEDICAL informatics; COMPUTER network resources; MEDICATION error prevention; INFORMATION storage &; retrieval systems; MEDICAL databases; AUTOMATION; DECISION support systems; MEDICAL students; STANDARDS
- Publication
BMC Medical Informatics & Decision Making, 2017, Vol 17, p1
- ISSN
1472-6947
- Publication type
journal article
- DOI
10.1186/s12911-017-0425-5