Algorithm-Driven Electronic Health Record Notification Enhances the Detection of Turner Syndrome

Eirene Alexandrou; Catalina Cabrera-Salcedo; Guillaume Labilloy; Leah Tyzinski; Teresa A Smolarek; Melissa Andrew; Yongbo Huang; Philippe Backeljauw; Andrew Dauber

doi:10.1016/j.jpeds.2019.09.023

Algorithm-Driven Electronic Health Record Notification Enhances the Detection of Turner Syndrome

J Pediatr. 2020 Jan:216:227-231. doi: 10.1016/j.jpeds.2019.09.023. Epub 2019 Oct 18.

Authors

Eirene Alexandrou¹, Catalina Cabrera-Salcedo², Guillaume Labilloy¹, Leah Tyzinski¹, Teresa A Smolarek³, Melissa Andrew⁴, Yongbo Huang¹, Philippe Backeljauw¹, Andrew Dauber⁵

Affiliations

¹ Cincinnati Children's Hospital Medical Center, Cincinnati, OH.
² Division of Endocrinology, University of Louisville, Louisville, KY.
³ Cincinnati Children's Hospital Medical Center, Cincinnati, OH; Department of Pediatrics, University of Cincinnati, Cincinnati, OH.
⁴ Division of Endocrinology, Children's National Health System, Washington, DC.
⁵ Division of Endocrinology, Children's National Health System, Washington, DC; Department of Pediatrics, George Washington School of Medicine and Health Sciences, Washington, DC. Electronic address: [email protected].

Abstract

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.

Publication types

Research Support, N.I.H., Extramural

MeSH terms

Adolescent
Algorithms*
Child
Child, Preschool
Early Diagnosis
Electronic Health Records*
Female
Humans
Turner Syndrome / diagnosis*

Grants and funding

R01 HD093622/HD/NICHD NIH HHS/United States