ArticleJournal of the American Medical Informatics Association : JAMIA2017
Learning from errors: analysis of medication order voiding in CPOE systems.
Article in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- A framework for developing, validating, and utilizing automated measures of order errors using the retract-and-reorder methodology.JAMIA open · 2026Article
- Automated search methods for identifying wrong patient order entry-a scoping review.JAMIA open · 2023Article
- Conceptual considerations for using EHR-based activity logs to measure clinician burnout and its effects.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Risk factors associated with medication ordering errors.Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Article
- Automated detection of wrong-drug prescribing errors.BMJ quality & safety · 2019Observational
- Contributions from the 2017 Literature on Clinical Decision Support.Yearbook of medical informatics · 2018Review
- Genomics and electronic health record systems.Human molecular genetics · 2018Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveMedication order voiding allows clinicians to indicate that an existing order was placed in error. We explored whether the order voiding function could be used to record and study medication ordering errors. MATERIALS AND
methodsWe examined medication orders from an academic medical center for a 6-year period (2006-2011; n = 5 804 150). We categorized orders based on status (void, not void) and clinician-provided reasons for voiding. We used multivariable logistic regression to investigate the association between order voiding and clinician, patient, and order characteristics. We conducted chart reviews on a random sample of voided orders ( n = 198) to investigate the rate of medication ordering errors among voided orders, and the accuracy of clinician-provided reasons for voiding.
resultsWe found that 0.49% of all orders were voided. Order voiding was associated with clinician type (physician, pharmacist, nurse, student, other) and order type (inpatient, prescription, home medications by history). An estimated 70 ± 10% of voided orders were due to medication ordering errors. Clinician-provided reasons for voiding were reasonably predictive of the actual cause of error for duplicate orders (72%), but not for other reasons. DISCUSSION AND
conclusionMedication safety initiatives require availability of error data to create repositories for learning and training. The voiding function is available in several electronic health record systems, so order voiding could provide a low-effort mechanism for self-reporting of medication ordering errors. Additional clinician training could help increase the quality of such reporting.
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