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. 2022 Jun 1;149(6):e2020014696.
doi: 10.1542/peds.2020-014696.

Reducing Pediatric Emergency Department Prescription Errors

Veena Devarajan  1 , Nicole L Nadeau  2 , Jessica K Creedon  3   4 , Timothy E Dribin  5   6 , Margaret Lin  7 , Alexander W Hirsch  3   4 , Jeffrey T Neal  3   4 , Amanda Stewart  3   4 , Erica Popovsky  8   9 , Danielle Levitt  10 , Jennifer A Hoffmann  8   9 , Michael Lee  3   4 , Catherine Perron  3   4 , Dhara Shah  11 , Matthew A Eisenberg  3   4 , Joel D Hudgins  3   4
Affiliations

Reducing Pediatric Emergency Department Prescription Errors

Veena Devarajan et al. Pediatrics. .

Abstract

Background: Prescription errors are a significant cause of iatrogenic harm in the health care system. Pediatric emergency department (ED) patients are particularly vulnerable to error. We sought to decrease prescription errors in an academic pediatric ED by 20% over a 24-month period by implementing identified national best practice guidelines.

Methods: From 2017 to 2019, a multidisciplinary, fellow-driven quality improvement (QI) project was conducted using the Model for Improvement. Four key drivers were identified including simplifying the electronic order entry into prescription folders, improving knowledge of dosing by indication, increasing error feedback to prescribers, and creating awareness of common prescription pitfalls. Four interventions were subsequently implemented. Outcome measures included prescription errors per 1000 prescriptions written for all medications and top 10 error-prone antibiotics. Process measures included provider awareness and use of prescription folders; the balancing measure was provider satisfaction. Differences in outcome measures were assessed by statistical process control methodology. Process and balancing measures were analyzed using 1-way analysis of variance and χ2 testing.

Results: Before our interventions, 8.6 errors per 1000 prescriptions written were identified, with 62% of errors from the top 10 most error-prone antibiotics. After interventions, error rate per 1000 prescriptions decreased from 8.6 to 4.5 overall and from 20.1 to 8.8 for top 10 error-prone antibiotics. Provider awareness of prescription folders was significantly increased.

Conclusion: QI efforts to implement previously defined best practices, including simplifying and standardizing computerized provider order entry (CPOE), significantly reduced prescription errors. Synergistic effect of educational and technological efforts likely contributed to the measured improvement.

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Conflict of interest statement

CONFLICT OF INTEREST DISCLOSURES: The authors have indicated they have no conflicts of interest relevant to this article to disclose.

Figures

FIGURE 1
FIGURE 1
Driver diagram identifying key drivers and categorized change strategies to reduce ED prescription errors.
FIGURE 2
FIGURE 2
Pareto chart of prescription errors by medication that show the frequency of error as well as their cumulative impact by percent. Top 10 error prone antibiotics are underlined on the X-axis.
FIGURE 3
FIGURE 3
Simplification of order entry by decreasing number of formulations and organizing medications into diagnosis-specific folders.
FIGURE 4
FIGURE 4
Medications and folders modified in each PDSA cycle. CPOE changes in PDSA cycle 1 and 2 focused on folders by indication, and PDSA cycle 3 involved broader medication classes.
FIGURE 5
FIGURE 5
Annotated statistical process control chart of prescription error rates for all medications.
FIGURE 6
FIGURE 6
Annotated statistical process control chart of prescription error rates for top error antibiotics.
See this image and copyright information in PMC

References

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