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Clinical validation of an electronic medical record-based asthma registry at a tertiary care center

Michael Aw1, Sumiya Lodhi2, Marielena Dibartolo2,3

  • 1Faculty of Medicine, Department of Internal Medicine, McGill University, Montreal, Canada.

The Journal of Asthma : Official Journal of the Association for the Care of Asthma
|March 18, 2026
PubMed

Insights

This study validated the Epic electronic medical record (EMR) asthma registry in children. The registry accurately identifies pediatric asthma patients, proving useful for clinical care and research.

Area of Science:

  • Pediatric Pulmonology
  • Health Informatics
  • Clinical Data Management

Background:

  • Large population-based asthma registries enhance disease understanding and management.
  • Electronic medical records (EMRs) offer a valuable resource for developing such registries.
  • The Children's Hospital of Eastern Ontario (CHEO) developed an Epic-EMR registry for pediatric asthma patients.

Purpose of the Study:

  • To validate the accuracy of the Epic-EMR asthma registry.
  • To compare the registry's diagnoses against expert clinical asthma diagnoses in children.
  • To assess the utility of the Epic-EMR registry for clinical care and research.

Main Methods:

  • A sample of 598 children aged 0-18 years was analyzed.
  • Children were randomly selected from the Epic-EMR asthma registry, non-asthma respiratory condition groups, and non-asthma, non-respiratory diagnosis groups.
  • Two blinded pediatric respirologists verified all asthma diagnoses using abstracted electronic chart data.

Main Results:

  • The Epic-EMR asthma registry demonstrated a positive predictive value of 0.91 and a negative predictive value of 0.92.
  • Overall specificity was high at 0.99, with sensitivity at 0.44.
  • Age-stratified analysis showed high specificity (0.99) and varying sensitivity (0.39 for 0-6 years, 0.5 for 6-18 years).

Conclusions:

  • The Epic-EMR asthma registry accurately identifies children with asthma.
  • The registry exhibits high specificity, positive predictive value, and negative predictive value.
  • This validated tool is suitable for use in clinical care and research settings for pediatric asthma.
Abstract

Keywords:
Electronic health recordsepic EMRregistry formationvalidation study

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