Title
Learning from errors: analysis of medication order voiding in CPOE systems.
Abstract
Objective: Medication 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 Methods: We 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. Results: We 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 Conclusion: Medication 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.
Year
DOI
Venue
2017
10.1093/jamia/ocw187
JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION
Keywords
Field
DocType
medication errors,patient safety,CPOE,medication order voiding
Data mining,Patient safety,Physical therapy,Pharmacist,Chart,Medical record,Retrospective cohort study,Logistic regression,Medicine,Medical prescription
Journal
Volume
Issue
ISSN
24
4
1067-5027
Citations 
PageRank 
References 
0
0.34
7
Authors
8