Researchers were better able to diagnose growth disorders and make specialized care decisions in children by using an algorithm built into an electronic health record, according to data published in JAMA.

“Monitoring of linear growth is a well-established part of pediatric health care in the developed world. Although monitoring aims to support early diagnosis and timely treatment of disorders affecting growth, such disorders are often diagnosed late,” Ulla Sankilampi, MD, PhD, from Kuopio University Hospital in Kuopio, Finland, and colleagues wrote.

The researchers conducted a 1-year prospective study of an automated growth monitoring intervention integrated into an EHR system in a primary care setting in Finland. They used the preceding 3-year period from 2005 to 2008, during which standard growth monitoring was used, as a comparator. An annual average of 33,029 children was evaluated during the 3-year comparator period.

The researchers reported 28 new diagnoses of a primary or secondary growth disorder among the 32,404 children screened during the automated growth monitoring intervention year. Of these, 88% were also evaluated during the comparator period. Fifty percent of the children who were newly diagnosed with a growth disorder during the intervention period had one or more abnormal height measurements before the automated growth monitoring intervention, with a median delay in diagnosis of 1.79 years, according to data.

“The diagnostic yield of primary or secondary growth disorders was 0.1 per 1,000 screened children in the control years vs. 0.9 per 1,000 in the [automated growth monitoring] year,” researchers wrote.

Data also indicate that a mean 72.7 referrals were made annually to a specialist for a growth disorder during the comparator period compared with 209 referrals during the automated growth monitoring year.

These findings demonstrate screening growth disorders by using EHRs were associated with a greater rate of diagnosis and referral to a specialist, researchers wrote.