Validating Coding for the Identification of Pediatric Treatment Resistant Epilepsy Patients

Daniel A Freedman1, Zachary Grinspan2, Peter Glynn3

  • 1Dell Medical School, The University of Texas at Austin, Austin, TX, USA.

Child Neurology Open
|September 13, 2021
PubMed

Insights

International Classification of Diseases (ICD) codes accurately identify individuals with treatment-resistant epilepsy. This study found high sensitivity and specificity, supporting their use in clinical trials and quality improvement initiatives.

Area of Science:

  • Neurology
  • Medical Informatics
  • Public Health

Background:

  • The International Classification of Diseases (ICD) system offers subcodes to denote treatment-resistant epilepsy.
  • Accurate identification of treatment-resistant epilepsy is crucial for quality improvement, population health management, and clinical trial recruitment.
  • The reliability of these ICD subcodes for identifying treatment-resistant epilepsy has not been clearly established.

Purpose of the Study:

  • To evaluate the accuracy of International Classification of Diseases (ICD) codes in identifying individuals with treatment-resistant epilepsy.
  • To assess the sensitivity and specificity of ICD codes for this specific patient population.

Main Methods:

  • A single-center, cross-sectional study was conducted.
  • 344 individuals were analyzed, with approximately half diagnosed with treatment-resistant epilepsy.
  • The accuracy of ICD codes was determined by comparing them against a clinical diagnosis.

Main Results:

  • The ICD codes demonstrated a sensitivity of 90% (147/164) and a specificity of 86% (155/180) for identifying treatment-resistant epilepsy.
  • Identified reasons for miscoding in children included epilepsy surgery, absence epilepsy, care by different providers, and recent visits to a movement disorders clinic.

Conclusions:

  • International Classification of Diseases (ICD) codes are a reliable tool for identifying individuals with treatment-resistant epilepsy.
  • The high accuracy supports the use of these codes in clinical practice for various healthcare management purposes.

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