Algorithm-driven electronic health record notification enhances the detection of Turner syndrome
Open accessAbstract
Early diagnosis of Turner syndrome enhances care, but in routine practice, even within larger referral centers, diagnosis is delayed. Our study examines the utility of an electronic health record algorithm in identifying patients at high risk for Turner syndrome. Six percent of those identified had missed diagnoses of Turner syndrome.
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An algorithm-driven electronic health record approach found that 6% of girls with microarray data available had newly diagnosed TS.
“The algorithm successfully found that 6% of girls with microarray data available had newly diagnosed TS, and that only 62% of girls with idiopathic short stature ever had a karyotype performed.”
From Clinical practice guidelines for the care of girls and women with Turner syndrome. (2024) · cites this paper as [101]
Only 62% of girls with idiopathic short stature ever had a karyotype performed.
“The algorithm successfully found that 6% of girls with microarray data available had newly diagnosed TS, and that only 62% of girls with idiopathic short stature ever had a karyotype performed.”
From Clinical practice guidelines for the care of girls and women with Turner syndrome. (2024) · cites this paper as [101]
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Self-citationThe effects of on-screen, point of care computer reminders on processes and outcomes of care
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Self-citationThe past, present, and future of child growth monitoring: A review and primer for clinical genetics
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Rare Disease Growth Monitoring: Improving Early Diagnosis
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Self-citation
- Authors
- Alexandrou, E., Cabrera-Salcedo, C., Labilloy, G., Tyzinski, L., Smolarek, T. A., Andrew, M., Huang, Y., Backeljauw, P., & Dauber, A.
- Affiliations
- Cincinnati Children's Hospital Medical Center (US)
- Children's National (US)
- Corresponding author
- Dauber, Andrew
- Venue
- The Journal of Pediatrics
- Publisher
- Elsevier BV
- Published
- 2020-01
- Volume
- 216
- Pages
- 227-231
- ISSN
- 0022-3476 (ISSN-L)
- PMC
- PMC7245696
- OpenAlex
- W2980495928
- Cited by
- 6
- References
- 12
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 2 · 2021: 2
- FWCI
- 0.55
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- The Journal of Pediatrics (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Ipsen Biopharmaceuticals
- Pfizer
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R01HD09362 2)
- Novo Nordisk
- Ipsen
- Sandoz
- Topics
- Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Sexual Differentiation and Disorders
- Keywords
- Turner syndrome, electronic health record algorithm, delayed diagnosis, missed diagnosis, high-risk patient identification, early diagnosis
- MeSH terms
- Adolescent, Algorithms, Child, Child, Preschool, Female, Humans, Turner Syndrome, Early Diagnosis, Electronic Health Records
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