Appropriateness of commercially available and partially customized medication dosing alerts among pediatric patients
Open accessAbstract
OBJECTIVES: To evaluate dosing alert appropriateness, categorize orders with alerts, and compare the appropriateness of alerts due to customized and non-customized dose ranges at a pediatric hospital. METHODS: This was a retrospective analysis of medication orders causing dosing alerts. Orders for outpatient prescriptions, patients ≥18 years of age, and research protocols were excluded. Patient medical records were reviewed and ordered doses compared with a widely used pediatric reference (Lexi-Comp) and institutional recommendations. The alerted orders were categorized and the occurrence of appropriate alerts was compared. RESULTS: There were 47 181 inpatient orders during the studied period; 1935 orders caused 3774 dosing alerts for 369 medications in 573 patients (median age 6.1 years). All alerted orders had an alert overridden by the prescriber. The majority (86.2%) of alerted orders inappropriately caused alerts; 58.0% were justifiable doses and 28.2% were within Lexi-Comp. However, 13.8% of alerted orders appropriately caused alerts; 8.0% were incorrect doses and 5.8% had no dosing recommendations available. Appropriately alerted orders occurred in 19.7% of alerted orders due to customized ranges compared to 12.8% due to non-customized ranges (p=0.002). Preterm and term neonates, infants, and children (2-5 years) had higher proportions of inappropriate alerts compared to appropriate alerts (all p<0.01). CONCLUSIONS: The vast majority of dosing alerts were presented to practitioners inappropriately, potentially contributing to alert fatigue. Appropriate alerts occurred more often when alerts were due to customized ranges. Advances in dosing alerts should aim to provide accurate and clinically relevant alerts that minimize excessive inappropriate alerting. Medications requiring dosing adjustments based on clinical parameters must be taken into account when designing and evaluating dosing alerts.
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A substantial body of work suggests that repeated CDSS alerts are less likely to be informative.
“This was because a substantial body of work [7, 8, 32, 33] suggests that repeated CDSS alerts are less likely to be informative (that is, they are often equivalent to false alarms).”
From Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system (2017) · cites this paper as [32]
The Discussion (page unavailable) reports that most pediatric dosing alerts studied were inappropriate and that excessive inappropriate alerting may contribute to alert fatigue. This supports the concern that many alerts are uninformative, but the paper does not establish that an alert becomes less informative when repeated. (LLM, conf=0.83)
Experimental — accuracy not yet measuredDuplicate alerts have previously been identified as potentially uninformative.
“Duplicate alerts have previously been identified as potentially uninformative [7, 8, 32].”
From Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system (2017) · cites this paper as [32]
The Discussion (page unavailable) identifies inappropriate pediatric dosing alerts as potentially contributing to alert fatigue, but does not identify duplicate alerts as uninformative. Searches for duplicate and redundant or repeated alerts found no passage addressing that specific claim. (LLM, conf=0.74)
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Cites
Incidence of Adverse Drug Events and Potential Adverse Drug Events: Implications for Prevention
Bates, D. W. (1995) · JAMA · doi:10.1001/jama.1995.03530010043033 · Cited by 2,127 · see citing works
Medication Errors and Adverse Drug Events in Pediatric Inpatients
Kaushal, R. (2001) · JAMA · doi:10.1001/jama.285.16.2114 · Cited by 1,917 · see citing works
Standard 6: Age Groups for Pediatric Trials
Williams, K. J., Thomson, D., Seto, I., Contopoulos-Ioannidis, D., Ioannidis, J., Curtis, S., Constantin, E., Batmanabane, G., Hartling, L., & Klassen, T. (2012) · Pediatrics · doi:10.1542/peds.2012-0055i · Cited by 504 · see citing works
Computerized Physician Order Entry and Medication Errors in a Pediatric Critical Care Unit
Potts, A. L., Barr, F. E., Gregory, D. F., Wright, L., & Patel, N. R. (2004) · Pediatrics · doi:10.1542/peds.113.1.59 · Cited by 410 · see citing works
Howard, D. P. J., Banerjee, A., Fairhead, J. F., Hands, L. J., Silver, L. E., & Rothwell, P. M. (2015) · Circulation · doi:10.1161/circulationaha.115.016424 · Cited by 325 · see citing works
Taketomo, C. K., Hodding, J., & Kraus, D. M. (1997) · Cited by 271 · see citing works
Tiering Drug-Drug Interaction Alerts by Severity Increases Compliance Rates
Paterno, M. D., Maviglia, S. M., Gorman, P. N., Seger, D. L., Yoshida, E., Seger, A. C., Bates, D. W., & Gandhi, T. K. (2009) · Journal of the American Medical Informatics Association · doi:10.1197/jamia.m2808 · Cited by 263 · see citing works
Strom, B. L., Schinnar, R., Aberra, F., Bilker, W., Hennessy, S., Leonard, C. E., & Pifer, E. (2010) · Archives of Internal Medicine · doi:10.1001/archinternmed.2010.324 · Cited by 217 · see citing works
Impact of Computerized Physician Order Entry on Clinical Practice in a Newborn Intensive Care Unit
Cordero, L., Kuehn, L., Kumar, R. R., & Mekhjian, H. S. (2004) · Journal of Perinatology · doi:10.1038/sj.jp.7211000 · Cited by 204 · see citing works
Effect of Computer Order Entry on Prevention of Serious Medication Errors in Hospitalized Children
Walsh, K. E., Landrigan, C. P., Adams, W. G., Vinci, R. J., Chessare, J. B., Cooper, M. R. C., Hebert, P. M., Schainker, E. G., McLaughlin, T., & Bauchner, H. (2008) · PEDIATRICS · doi:10.1542/peds.2007-0220 · Cited by 170 · see citing works
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
Cash, J. J. (2009) · American Journal of Health-System Pharmacy · doi:10.2146/ajhp090181 · Cited by 126 · see citing works
Upperman, J. S., Staley, P., Friend, K., Neches, W. H., Kazimer, D., Benes, J., & Wiener, E. S. (2005) · Journal of Pediatric Surgery · doi:10.1016/j.jpedsurg.2004.09.024 · Cited by 121 · see citing works
Kazemi, A., Ellenius, J., Pourasghar, F., Tofighi, S., Salehi, A., Amanati, A., & Fors, U. (2009) · Journal of Medical Systems · doi:10.1007/s10916-009-9338-x · Cited by 95 · see citing works
Frequency and Preventability of Adverse Drug Reactions in Paediatric Patients
Temple, M. E., Robinson, R. F., Miller, J. C., et al. (2004) · Drug Safety · doi:10.2165/00002018-200427110-00005 · Cited by 90 · see citing works
Computerized Order Entry With Limited Decision Support to Prevent Prescription Errors in a PICU
Kadmon, G., Bron‐Harlev, E., Nahum, E., Schiller, O., Haski, G., & Shonfeld, T. (2009) · PEDIATRICS · doi:10.1542/peds.2008-2737 · Cited by 89 · see citing works
Computerized clinical decision support for medication prescribing and utilization in pediatrics
Stultz, J. S., & Nahata, M. C. (2012) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000798 · Cited by 67 · see citing works
Self-citationSmithburger, P. L., Kane‐Gill, S. L., Benedict, N. J., Falcione, B. A., & Seybert, A. L. (2010) · Annals of Pharmacotherapy · doi:10.1345/aph.1p377 · Cited by 62 · see citing works
Jani, Y. H., Barber, N., & Wong, I. C. K. (2011) · International Journal of Pharmacy Practice · doi:10.1111/j.2042-7174.2011.00132.x · Cited by 44 · see citing works
Automated Dose-Rounding Recommendations for Pediatric Medications
Johnson, K. B., Lee, C. K. K., Spooner, S. A., et al. (2011) · PEDIATRICS · doi:10.1542/peds.2011-0760 · Cited by 40 · see citing works
To What Extent Do Pediatricians Accept Computer-Based Dosing Suggestions?
Killelea, B. K., Kaushal, R., Cooper, M. R., et al. (2007) · PEDIATRICS · doi:10.1542/peds.2006-1388 · Cited by 38 · see citing works
Ferranti, J. M., Horvath, M. M., Jansen, J., Schellenberger, P., Brown, T., DeRienzo, C. M., & Ahmad, A. (2011) · BMC Medical Informatics and Decision Making · doi:10.1186/1472-6947-11-14 · Cited by 30 · see citing works
Evaluation of Contraindicated Drug-Drug Interaction Alerts in a Hospital Setting
Hatton, R. C., Rosenberg, A. F., Morris, C. T., McKelvey, R. P., & Lewis, J. R. (2011) · Annals of Pharmacotherapy · doi:10.1345/aph.1p533 · Cited by 25 · see citing works
Fatal hyperphosphatemia after oral phosphate overdose in a premature infant
Perlman, J. M. (1997) · American Journal of Health-System Pharmacy · doi:10.1093/ajhp/54.21.2488 · Cited by 24 · see citing works
Graphical user interface for a neonatal parenteral nutrition decision support system.
Peverini, R. L., Beach, D. S., Wan, K., et al. (2000) · PubMed · Cited by 23 · see citing works
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with the HITEC Investigators, Ancker, J. S., Edwards, A., Nosal, S., Hauser, D., Mauer, E., & Kaushal, R. (2017) · BMC Medical Informatics and Decision Making · doi:10.1186/s12911-017-0430-8 · Cited by 709 · see citing works
“We considered alerts that were repeated the same year as potentially uninformative, following the work of previous researchers who have identified repeated alerts as duplicative and likely to have low relevance [7, 8, 32, 33].”
BackgroundOlakotan, O. O., & Mohd Yusof, M. (2021) · Health Informatics Journal · doi:10.1177/14604582211007536 · Cited by 101 · see citing works
- Authors
- Stultz, J. S., & Nahata, M. C.
- Affiliations
- Nationwide Children's Hospital (US)
- The Ohio State University (US)
- Corresponding author
- Nahata, Milap C
- ORCID
- Stultz, Jeremy S
- Venue
- Journal of the American Medical Informatics Association
- Publisher
- Oxford University Press (OUP)
- Published
- 2014-02
- Volume
- 21
- Issue
- e1
- Pages
- e35-e42
- ISSN
- 1067-5027 (ISSN-L)
- 1527-974X
- PMC
- PMC3957387
- OpenAlex
- W2126525023
- Cited by
- 28
- References
- 25
- Citations by year
- 2025: 1 · 2024: 3 · 2023: 2 · 2022: 2 · 2021: 1 · 2020: 2 · 2019: 3 · 2018: 3 · 2017: 3 · 2016: 1 · 2015: 3 · 2014: 4
- FWCI
- 4.62
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of the American Medical Informatics Association (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Ohio State University
- Nationwide Children's Hospital
- 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 › Pediatrics, Perinatology and Child Health › Pharmaceutical studies and practices
- Keywords
- pediatric dosing, alarm fatigue, medication order review, alert override, neonates and infants, clinical decision support
- MeSH terms
- Child, Child, Preschool, Pharmaceutical Preparations, Female, Hospitals, Pediatric, Humans, Infant, Infant, Newborn, Male, Medication Errors, Medication Systems, Hospital, Retrospective Studies, Reminder Systems, Medical Order Entry Systems, Electronic Health Records
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