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A Clinical Case of Electronic Health Record Drug Alert Fatigue: Consequences for Patient Outcome
Abstract
Despite advances in electronic medication order entry systems, it has been well established that clinicians override many drug allergy alerts generated by the electronic health record. The direct clinical consequences of overalerting clinicians in a pediatric setting have not been well demonstrated in the literature. We observed a patient in the PICU who experienced complications as a result of an extended series of non–evidence-based alerts in the electronic health record. Subsequently, evidence-based allergy alerting changes were made to the hospital’s system. Incorporating clinical evidence in electronic drug allergy alerting systems remains challenging, especially in pediatric settings.
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In the citing paper
“It is widely accepted that “alert fatigue” explains high override rates [7, 9–14].”
From Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system (2017) · cites this paper as [9]
In the citing paper
“A second conceptual model of alert fatigue is that repeated exposure to alerts leads to declining responsiveness [9, 19, 20], a phenomenon that can be called desensitization .”
From Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system (2017) · cites this paper as [9]
In the citing paper
“Application of AI systems in the real world may lead to many unintended outcomes, including alert fatigue,131 additional burdens for clinicians, disruption of interpersonal communications, and generation of specific threats requiring increased vigilance to recognize.132”
From Artificial intelligence in diabetes management: Advancements, opportunities, and challenges (2023) · cites this paper as [131]
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Cites
Garg, A. X., Adhikari, N. K. J., McDonald, H., Rosas-Arellano, M. P., Devereaux, P. J., Beyene, J., Sam, J., & Haynes, R. B. (2005) · JAMA · doi:10.1001/jama.293.10.1223 · Cited by 2,936
Improving Safety with Information Technology
Bates, D. W., & Gawande, A. A. (2003) · New England Journal of Medicine · doi:10.1056/nejmsa020847 · Cited by 1,544
Data-driven prediction of drug effects and interactions
Tatonetti, N. P., Ye, P. P., Daneshjou, R., & Altman, R. B. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3003377 · Cited by 936
Physicians' Decisions to Override Computerized Drug Alerts in Primary Care
Weingart, S. N., Toth, M., Sands, D. Z., Aronson, M. D., Davis, R. B., & Phillips, R. S. (2003) · Archives of Internal Medicine · doi:10.1001/archinte.163.21.2625 · Cited by 487
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
Absence of Cross-Reactivity between Sulfonamide Antibiotics and Sulfonamide Nonantibiotics
Strom, B. L., Schinnar, R., Apter, A. J., Margolis, D. J., Lautenbach, E., Hennessy, S., Bilker, W. B., & Pettitt, D. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa022963 · Cited by 349
Horsky, J., Schiff, G. D., Johnston, D., Mercincavage, L. M., Bell, D. S., & Middleton, B. (2012) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2012.09.002 · Cited by 307
Kesselheim, A. S., Cresswell, K., Phansalkar, S., Bates, D. W., & Sheikh, A. (2011) · Health Affairs · doi:10.1377/hlthaff.2010.1111 · Cited by 277
Schedlbauer, A., Prasad, V., Mulvaney, C., Phansalkar, S., Stanton, W., Bates, D. W., & Avery, A. J. (2009) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2910 · Cited by 262
Hsieh, T. C., Kuperman, G. J., Jaggi, T., Hojnowski-Diaz, P., Fiskio, J., Williams, D. H., Bates, D. W., & Gandhi, T. K. (2004) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m1556 · Cited by 232
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Medication-related clinical decision support alert overrides in inpatients
Nanji, K. C., Seger, D. L., Slight, S. P., Amato, M. G., Beeler, P. E., Her, Q. L., Dalleur, O., Eguale, T., Wong, A., Silvers, E. R., et al. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocx115 · Cited by 179
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Integrating pharmacogenomics into electronic health records with clinical decision support
Hicks, J. K., Dunnenberger, H. M., Gumpper, K. F., Haidar, C. E., & Hoffman, J. M. (2016) · American Journal of Health-System Pharmacy · doi:10.2146/ajhp160030 · Cited by 175
McGreevey, J. D., Mallozzi, C. P., Perkins, R. M., Shelov, E., & Schreiber, R. (2020) · Applied Clinical Informatics · doi:10.1055/s-0039-3402715 · Cited by 165
The influence of electronic health record use on collaboration among medical specialties
Vos, J. F. J., Boonstra, A., Kooistra, A. M. D., Seelen, M. A., & Offenbeek, V. M. (2020) · BMC Health Services Research · doi:10.1186/s12913-020-05542-6 · Cited by 142
Henry, K. E., Adams, R., Parent, C., Soleimani, H., Sridharan, A., Johnson, L., Hager, D. N., Cosgrove, S. E., Markowski, A., Klein, E. Y., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01895-z · Cited by 144
Kane‐Gill, S. L., O’Connor, M. F., Rothschild, J. M., Selby, N. M., McLean, B. A., Bonafide, C. P., Cvach, M. M., Hu, X., Konkani, A., Pelter, M. M., et al. (2017) · Critical Care Medicine · doi:10.1097/ccm.0000000000002580 · Cited by 121
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Légat, L., Laere, S. V., Nyssen, M., Steurbaut, S., Dupont, A. G., & Cornu, P. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.8206 · Cited by 98
Hartzler, A. L., McCarty, C. A., Rasmussen, L. V., Williams, M. S., Brilliant, M. H., Bowton, E., Clayton, E. W., Faucett, W. A., Ferry, K., Field, J. R., et al. (2013) · Genetics in Medicine · doi:10.1038/gim.2013.127 · Cited by 80
Sittig, D. F., Ash, J. S., & Singh, H. (2014) · PubMed · Cited by 74
Ip, I. K., Raja, A. S., Gupta, A., Andruchow, J. E., Sodickson, A. D., & Khorasani, R. (2014) · The American Journal of Emergency Medicine · doi:10.1016/j.ajem.2014.11.005 · Cited by 67
Electronic health record usability, satisfaction, and burnout for family physicians.
Holmgren, A. J., Hendrix, N., Maisel, N., Everson, J., Bazemore, A., Rotenstein, L., Phillips, R. L., & Adler-Milstein, J. (2024) · JAMA Network Open · doi:10.1001/jamanetworkopen.2024.26956 · Cited by 56
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Brady, T. M., Neu, A. M., Miller, E. R., Appel, L. J., Siberry, G. K., & Solomon, B. S. (2014) · Clinical Pediatrics · doi:10.1177/0009922814559379 · Cited by 52
McDaniel, R. B., Burlison, J. D., Baker, D. K., Hasan, M., Robertson, J., Hartford, C. M., Howard, S. C., Sablauer, A., & Hoffman, J. M. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv144 · Cited by 47
Slight, S. P., Beeler, P. E., Seger, D. L., Amato, M. G., Her, Q. L., Swerdloff, M., Dalleur, O., Nanji, K. C., Cho, I., Maniam, N., et al. (2016) · BMJ Quality & Safety · doi:10.1136/bmjqs-2015-004851 · Cited by 44
A Model to Support Shared Decision Making in Electronic Health Records Systems
Lenert, L. A., Dunlea, R., Fiol, G. D., & Hall, L. K. (2014) · Medical Decision Making · doi:10.1177/0272989x14550102 · Cited by 46
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Chaparro, J. D., Classen, D. C., Danforth, M., Stockwell, D. C., & Longhurst, C. (2016) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocw134 · Cited by 38
Self-citationDevin, J. E., Cleary, B., & Cullinan, S. (2020) · Systematic Reviews · doi:10.1186/s13643-020-01510-7 · Cited by 39
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Goel, A., Sanchez, J., Paulino, L., Feuille, C. J., Arend, J., Shah, B., Dieterich, D. T., & Perumalswami, P. (2016) · Journal of Viral Hepatitis · doi:10.1111/jvh.12669 · Cited by 35
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Martin, M. C., & Wilson, F. P. (2018) · Clinical Journal of the American Society of Nephrology · doi:10.2215/cjn.13841217 · Cited by 33
Holmgren, A. J., Co, Z., Newmark, L. P., Danforth, M., Classen, D. C., & Bates, D. W. (2019) · BMJ Quality & Safety · doi:10.1136/bmjqs-2019-009609 · Cited by 37
Chen, C., Chen, Y.-L., Scholl, J., Yang, H., & Li, Y. (2023) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2023.107869 · Cited by 33
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Chai, P. R., Zhang, H., Baugh, C. W., Jambaulikar, G. D., McCabe, J., Gorman, J. M., Boyer, E. W., & Landman, A. (2018) · Journal of Medical Internet Research · doi:10.2196/jmir.9454 · Cited by 27
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Orenstein, E. W., Kandaswamy, S., Muthu, N., Chaparro, J. D., Hagedorn, P. A., Dziorny, A. C., Moses, A., Hernandez, S., Khan, A. N., Huth, H. B., et al. (2021) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocab179 · Cited by 27
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Self-citationRayo, M. F., Kowalczyk, N. K., Liston, B. W., Sanders, E., White, S., & Patterson, E. S. (2015) · Human Factors The Journal of the Human Factors and Ergonomics Society · doi:10.1177/0018720815585666 · Cited by 28
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Balestra, M., Chen, J., Iturrate, E., Aphinyanaphongs, Y., & Nov, O. (2021) · JAMIA Open · doi:10.1093/jamiaopen/ooab083 · Cited by 25
Nishimura, A. A., Shirts, B. H., Salama, J. S., Smith, J. W., Devine, B., & Tarczy-Hornoch, P. Z. (2015) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2015.11.004 · Cited by 23
Fallon, A., Haralambides, K., Mazzillo, J., & Gleber, C. (2024) · Applied Clinical Informatics · doi:10.1055/a-2226-8144 · Cited by 22
Mutter, M., Martin, M. C., Yamamoto, Y., Biswas, A., Etropolski, B., Feldman, H. I., Garg, A. X., Gourlie, N. M., Latham, S. R., Lin, H., et al. (2019) · BMJ Open · doi:10.1136/bmjopen-2018-025117 · Cited by 22
Knight, A. M., Maygers, J., Foltz, K. A., John, I. S., Yeh, H. C., & Brotman, D. J. (2019) · Applied Clinical Informatics · doi:10.1055/s-0039-3400447 · Cited by 22
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Wasylewicz, A. T. M., van de Burgt, B. W. M., Manten, T., Kerskes, M., Compagner, W. N., Korsten, E. H. H. M., Egberts, T. C. G., & Grouls, R. J. E. (2022) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.2624 · Cited by 20
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Goss, F. R., Bookman, K. J., Barron, M. A., Bickley, D., Landgren, B., Kroehl, M., Williamson, K. M., Zane, R. D., & Wiler, J. L. (2020) · Journal of the American College of Emergency Physicians Open · doi:10.1002/emp2.12029 · Cited by 19
Horng, S., Joseph, J. W., Calder, S., Stevens, J. P., O’Donoghue, A. L., Safran, C., Nathanson, L. A., & Leventhal, E. L. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.16499 · Cited by 21
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Mitchell, J. L., de Quincey, E., Pantin, C. T., & Mustfa, N. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-49757-6_21 · Cited by 7
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Metadata
- Authors
- Carspecken, C. W., Sharek, P. J., Longhurst, C., & Pageler, N. M.
- Affiliations
- Harvard University (US)
- Lucile Packard Children's Hospital (US)
- Systems Medicine, and
- Stanford Medicine (US)
- ORCID
- Pageler, Natalie M.
- Venue
- Pediatrics
- Publisher
- American Academy of Pediatrics (AAP)
- Published
- 2013-06-01
- Volume
- 131
- Issue
- 6
- Pages
- e1970-e1973
- ISSN
- 0031-4005 (ISSN-L)
- 1098-4275
- OpenAlex
- W2047955590
- Cited by
- 142
- References
- 22
- Citations by year
- 2026: 9 · 2025: 9 · 2024: 9 · 2023: 11 · 2022: 11 · 2021: 10 · 2020: 15 · 2019: 11 · 2018: 8 · 2017: 11 · 2016: 11 · 2015: 17 · 2014: 8 · 2013: 2
- FWCI
- 21.92
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- PEDIATRICS (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Patient Safety and Medication Errors
- Health Sciences › Medicine › Pharmacology (medical) › Drug-Induced Adverse Reactions
- Keywords
- drug allergy alerts, electronic health records, alarm fatigue, alert override, pediatric intensive care unit, drug safety, patient outcomes
- MeSH terms
- Child, Preschool, Diagnosis, Differential, Drug Hypersensitivity, Fatigue, Humans, Male, Medication Errors, Practice Patterns, Physicians', Evidence-Based Medicine, Decision Support Systems, Clinical, Medical Order Entry Systems, Electronic Health Records
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