Accuracy of Asthma Computable Phenotypes to Identify Pediatric Asthma at an Academic Institution.

Journal: Methods of information in medicine
Published Date: Dec 1, 2020

Abstract

OBJECTIVES: Asthma is a heterogenous condition with significant diagnostic complexity, including variations in symptoms and temporal criteria. The disease can be difficult for clinicians to diagnose accurately. Properly identifying asthma patients from the electronic health record is consequently challenging as current algorithms (computable phenotypes) rely on diagnostic codes (e.g., International Classification of Disease, ICD) in addition to other criteria (e.g., inhaler medications)-but presume an accurate diagnosis. As such, there is no universally accepted or rigorously tested computable phenotype for asthma.

Authors

  • Mindy K Ross
    1 Department of Pediatrics, Division of Pediatric Pulmonology and Sleep Medicine, and.
  • Henry Zheng
    Department of Radiological Sciences, University of California Los Angeles, Los Angeles, California, United States.
  • Bing Zhu
    Department of Gynecology, the First People's Hospital of Shangqiu, Shangqiu, Henan, People's Republic of China.
  • Ailina Lao
    University of California Los Angeles, Los Angeles, California, United States.
  • Hyejin Hong
    University of California Los Angeles, Los Angeles, California, United States.
  • Alamelu Natesan
    Department of Pediatrics, University of California Los Angeles, Los Angeles, California, United States.
  • Melina Radparvar
    Department of Pediatrics, University of California Los Angeles, Los Angeles, California, United States.
  • Alex A T Bui

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