A study of the frequency and rationale for overriding allergy warnings in a computerized prescriber order entry system
Abstract
Objectives: The goal of this 2-part study was to quantify the frequency of allergy warnings that were overridden, specify the reasons why a clinician chose to override an alert, and evaluate allergy warnings that were accepted by prescribers. Methods: This was a retrospective analysis of computerized prescriber order entry decision support allergy warnings and the corresponding prescriber decisions during four 1-week intervals and another 16-week interval from August 2003 to February 2005 at a 993-bed tertiary care teaching hospital. The following information was collected: patient allergy status, allergy category, allergy severity, warning provided, clinician category, and the reason warning was overridden. Results: A total of 29,483 evaluated orders triggered 777 allergy warnings, of which, 44% of the warnings were accepted, and 56% of the warnings were overridden. Of the 435 warnings that were overridden by the ordering clinician, 6% of the warnings were drug specific, and 94% were drug class warnings. The primary reason selected for overriding an allergy warning was that the patient tolerated the medication in the past (70%). Of the 342 warnings that were accepted by ordering clinicians, 24% of the warnings were drug specific, and 76% were drug class warnings. Conclusions: Clinicians were much less likely to override a warning if it was an exact drug match compared with a drug class warning. Limiting the number of alerts for less significant drug class warnings would help…
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Alert nonadherence, or clinician overrides, occurs for 49%-96% of alerts.
“Alert nonadherence, or clinician overrides, is one key barrier that occurs for 49%–96% of alerts.13–23”
From Clinician collaboration to improve clinical decision support: the Clickbusters initiative (2022) · cites this paper as [22]
Cites
Improving Acceptance of Computerized Prescribing Alerts in Ambulatory Care
Shah, N. R., Seger, A. C., Seger, D. L., Fiskio, J. M., Kuperman, G. J., Blumenfeld, B., Recklet, E. G., Bates, D. W., & Gandhi, T. K. (2006) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m1868 · Cited by 353 · see citing works
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A framework for evaluating the appropriateness of clinical decision support alerts and responses
McCoy, A. B., Waitman, L. R., Lewis, J. B., Wright, J. A., Choma, D. P., Miller, R. A., & Peterson, J. F. (2012) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000185 · Cited by 138 · see citing works
Clinician collaboration to improve clinical decision support: the Clickbusters initiative
McCoy, A. B., Russo, E. M., Johnson, K. B., Addison, B., Patel, N., Wanderer, J. P., Mize, D. E., Jackson, J. G., Reese, T. J., Littlejohn, S., et al. (2022) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocac027 · Cited by 41 · see citing works
- Authors
- Swiderski, S. M., Pedersen, C. A., Schneider, P. J., & Miller, A. S.
- Affiliations
- The Ohio State University Wexner Medical Center (US)
- The Ohio State University (US)
- Corresponding author
- Swiderski, Samantha M.
- Pedersen, Craig A.
- Schneider, Philip J.
- Venue
- Journal of Patient Safety
- Published
- 2007-06
- Volume
- 3
- Issue
- 2
- Pages
- 91-96
- ISSN
- 1549-8417 (ISSN-L)
- OpenAlex
- W2089946165
- Cited by
- 11
- References
- 1
- Citations by year
- 2023: 1 · 2022: 1 · 2021: 1 · 2018: 1 · 2014: 1
- FWCI
- 3.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Patient Safety (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Health Professions › Emergency Medical Services › Patient Safety and Medication Errors
- Health Sciences › Medicine › Pharmacology › Drug-Induced Adverse Reactions
- Keywords
- computerized physician order entry, clinical decision support, drug hypersensitivity, prescriber behavior, drug safety, positive predictive value
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