137 Accuracy of using administrative data to identify epilepsy cases: a systematic review of validation studies

Abstract

PurposeTo ascertain the accuracy of using administrative healthcare data to identify epilepsy cases.MethodWe searched MEDLINE and Embase from 01/01/1975–03/07/2018 for studies evaluating the diagnostic accuracy of administrative data in identifying epilepsy cases using any disease coding system. Two authors independently screened studies, extracted data, and quality-assessed studies. We assessed PPV, sensitivity, NPV, and specificity. The primary analysis was narrative.ResultsThirty studies were included between 1989–2018. Risks of bias were low, high, and unclear in four, 14, and 12 studies, respectively. Coding systems included ICD-9, ICD-10 and Read Codes, with or without antiepileptic drugs (AEDs). PPVs included ranges of 5.2–100% (Canada), 32.7–96.0% (US), 47.0–100% (UK), and 37.0–88.0% (Norway). Sensitivities included ranges of 22.2–99.7% (Canada), 12.2–97.3% (US), and 79.0–94.0% (UK). Nineteen studies contained ≥1 algorithm with a PPV >80%. Sixteen studies contained ≥1 algorithm with a sensitivity >80%. PPV was highest in algorithms consisting of disease codes (ICD-10 G40–41, ICD-9 345) in combination with ≥1 AED. The addition of symptom codes to this (ICD-10 R56, ICD-9 780.3, 780.39) lowered PPV. Sensitivity was highest in algorithms consisting of symptom codes with ≥1 AED. Whilst using AEDs alone achieved high sensitivities, the associated PPVs were low. Most NPVs and specificities were >90%.ConclusionIn the first global systematic review of this topic, we conclude that it is reasonable to use administrative data to identify people with epilepsy in epidemiological research.mbizvogkm@gmail.com