Improving Acceptance of Computerized Prescribing Alerts in Ambulatory Care
Open accessAbstract
Computerized drug prescribing alerts can improve patient safety, but are often overridden because of poor specificity and alert overload. Our objective was to improve clinician acceptance of drug alerts by designing a selective set of drug alerts for the ambulatory care setting and minimizing workflow disruptions by designating only critical to high-severity alerts to be interruptive to clinician workflow. The alerts were presented to clinicians using computerized prescribing within an electronic medical record in 31 Boston-area practices. There were 18,115 drug alerts generated during our six-month study period. Of these, 12,933 (71%) were noninterruptive and 5,182 (29%) interruptive. Of the 5,182 interruptive alerts, 67% were accepted. Reasons for overrides varied for each drug alert category and provided potentially useful information for future alert improvement. These data suggest that it is possible to design computerized prescribing decision support with high rates of alert recommendation acceptance by clinicians.
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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 [21]
Table 3 (Methods) reports clinician overrides, including rates of 58% for drug–drug alerts and 90% for drug-pregnancy alerts. But its overall override rate for interruptive alerts is 33%, and no reported category reaches 96%, so this paper does not support the stated 49%–96% range as a general rate. (LLM, conf=0.87)
Experimental — accuracy not yet measuredThe overall override rate in this study is at the lower end of what is reported in the literature but higher than the rate reported from the authors' ambulatory care practices in a prior 2006 study.
“While the overall override rate in this study is at the lower end of what is reported in the literature, it is higher than the rate we reported from our ambulatory care practices in a prior study in 2006.14”
From Overrides of medication-related clinical decision support alerts in outpatients (2014) · cites this paper as [14]
In the prior 2006 study, 33% of interruptive CDS alerts in outpatient systems were overridden, with override rates ranging from 23% for duplicate class warnings to 90% for drug-pregnancy interactions.
“At that time, we found that 33% of interruptive CDS alerts in outpatient systems were overridden, with override rates ranging widely by the type of warning, from 23% for duplicate class warnings to 90% for drug-pregnancy interactions.14”
From Overrides of medication-related clinical decision support alerts in outpatients (2014) · cites this paper as [14]
Although the authors have extensively modified the CDS system at their center to promote user acceptance and reduce alert fatigue, they have continued to observe a high level of CDS alert overrides.
“Furthermore, although we have extensively modified the CDS system at our center to promote user acceptance and reduce alert fatigue, 13 we have continued to observe a high level of CDS alert overrides.14”
From Overrides of medication-related clinical decision support alerts in outpatients (2014) · cites this paper as [14]
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- Authors
- 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.
- Affiliations
- Brigham and Women's Hospital (US)
- Corresponding author
- Gandhi, Tejal K.
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2006-01
- Volume
- 13
- Issue
- 1
- Pages
- 5-11
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC1380196
- OpenAlex
- W2131675703
- Cited by
- 353
- References
- 22
- Citations by year
- 2026: 2 · 2025: 5 · 2024: 6 · 2023: 9 · 2022: 14 · 2021: 14 · 2020: 7 · 2019: 12 · 2018: 8 · 2017: 16 · 2016: 23 · 2015: 25 · 2014: 24 · 2013: 32 · 2012: 40
- FWCI
- 22.35
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Agency for Healthcare Research and Quality (2t32hs000020-18, R01-HS1169)
- 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 › Geriatrics and Gerontology › Pharmaceutical Practices and Patient Outcomes
- Keywords
- drug alerts, alert override, clinician acceptance, interruptive alerts, electronic health records, outpatient care, patient safety, workflow disruption
- MeSH terms
- Contraindications, Adult, Ambulatory Care Information Systems, Attitude of Health Personnel, Attitude to Computers, Drug Therapy, Computer-Assisted, Pharmaceutical Preparations, Female, Humans, Medication Errors, Pregnancy, Drug Prescriptions, Primary Health Care, User-Computer Interface, Medical Records Systems, Computerized, Reminder Systems, Medical Order Entry Systems
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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