How accurate is ICD coding for epilepsy?

Nathalie Jetté, Aylin Y. Reid, Hude Quan, Michael D. Hill, Samuel Wiebe

Research output: Contribution to journalArticlepeer-review

161 Scopus citations

Abstract

Purpose: Assess the validity of ICD-9-CM and ICD-10 epilepsy coding from an emergency visit (ER) and a hospital discharge abstract database (DAD). Methods: Two separate sources of patient records were reviewed and validated. (1) Charts of patients admitted to our seizure monitoring unit over 2 years (n = 127, ICD-10 coded records) were reviewed. Sensitivity (Sn), specificity (Sp), and positive and negative predictive values (PPV and NPV) were calculated. (2) Random sample of charts for patients seen in the ER or admitted to hospital under any services, and whose charts were coded with epilepsy or an epilepsy-like condition, were reviewed. Two time-periods were selected to allow validation of both ICD-9-CM (n = 486) and ICD-10 coded (n = 454) records. Only PPV and NPV were calculated for these records. All charts were reviewed by two physicians to confirm the presence/absence of epilepsy and compare to administrative coding. Results: Sample 1: Sn, Sp, PPV, and NPV of ICD-10 epilepsy coding from the seizure monitoring unit (SMU) chart review were 99%, 70%, 85%, and 97% respectively. Sample 2: The PPV and NPV for ICD-9-CM coding from the ER database were, respectively, 99% and 97% and from the DAD were 98% and 99%. The PPV and NPV for ICD-10 coding from the ER database were, respectively, 100% and 90% and from the DAD were 98% and 99%. The epilepsy subtypes grand mal status and partial epilepsy with complex partial seizures both had PPVs >75% (ICD-9-CM and ICD-10 data). Discussion: Administrative emergency and hospital discharge data have high epilepsy coding validity overall in our health region.

Original languageEnglish
Pages (from-to)62-69
Number of pages8
JournalEpilepsia
Volume51
Issue number1
DOIs
StatePublished - 2010
Externally publishedYes

Keywords

  • Administrative data
  • International classification of diseases
  • Surveillance
  • Validation

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