Algorithm-driven electronic health record notification enhances detection of Turner syndrome

Abstract

Causes for short stature in females are numerous; Turner syndrome is among the commoner etiologies. A simple blood test, array comparative genomic hybridization (aCGH, commonly called "microarray") or karyotype, can typically identify partial or complete absence of the second sex chromosome. Chromosome analysis has been a standard recommendation in evaluating idiopathic proportional short stature in females (J Clin Endocrinol Metab 2008;93:4210–7) (Genet Med 2009;11:465–70). In this volume of The Journal, Alexandrou et al used an algorithm-driven review of electronic health records (EHRs) to identify 216 females with idiopathic short stature, of which 72 females had never received chromosome analysis. Interestingly, the females who received chromosome analysis were significantly shorter with a greater mid-parental height deflection than those who had not received either microarray or karyotype. Of the 72 patients initially identified without chromosome analysis, 32 were successfully studied with aCGH. Of these, 2 new cases of Turner syndrome were identified and 1 new patient had a chromosome copy number variant associated with short stature. This study demonstrates the power of EHRs in capturing signs and symptoms of unrecognized diseases. As the completeness of EHRs becomes widespread, the strategy of recognizing overlooked healthcare needs by searching for signs in the EHR may be more frequently used. This strategy can also identify deviation from disease-specific guidelines and help to create systematic compliance with standards of care. In this study, one-third of females with idiopathic short stature did not receive the recommended (10 years ago) chromosome analysis in their initial evaluations. EHR-driven strategies could help compliance with disease-specific guidelines and serve as a focus for quality improvement. Article page 227▸ Algorithm-Driven Electronic Health Record Notification Enhances the Detection of Turner SyndromeThe Journal of PediatricsVol. 216PreviewEarly 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. Full-Text PDF