Validating epilepsy diagnoses in routinely collected data

Fonferko-Shadrach, Beata, Lacey, Arron S., White, Catharine P., Powell, H.W. Rob, Sawhney, Inder M.S., Lyons, Ronan A., Smith, Phil E. M. ORCID: https://orcid.org/0000-0003-4250-2562, Kerr, Michael P., Rees, Mark I. and Pickrell, W. Owen 2017. Validating epilepsy diagnoses in routinely collected data. Seizure 52 , pp. 195-196. 10.1016/j.seizure.2017.10.008

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Abstract

Purpose: Anonymised, routinely-collected healthcare data is increasingly being used for epilepsy research. We validated algorithms using general practitioner (GP) primary healthcare records to identify people with epilepsy from anonymised healthcare data within the Secure Anonymised Information Linkage (SAIL) databank in Wales, UK. Method: A reference population of 150 people with definite epilepsy and 150 people without epilepsy was ascertained from hospital records and linked to records contained within SAIL (containing GP records for 2.4 million people). We used three different algorithms, using combinations of GP epilepsy diagnosis and anti-epileptic drug (AED) prescription codes, to identify the reference population. Results: Combining diagnosis and AED prescription codes had a sensitivity of 84% (95% ci 77–90) and specificity of 98% (95–100) in identifying people with epilepsy; diagnosis codes alone had a sensitivity of 86% (80–91) and a specificity of 97% (92–99); and AED prescription codes alone achieved a sensitivity of 92% (70–83) and a specificity of 73% (65–80). Using AED codes only was more accurate in children achieving a sensitivity of 88% (75–95) and specificity of 98% (88–100). Conclusion: GP epilepsy diagnosis and AED prescription codes can be confidently used to identify people with epilepsy using anonymised healthcare records in Wales, UK

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Medicine MRC Centre for Neuropsychiatric Genetics and Genomics (CNGG)
Publisher:	Elsevier
ISSN:	1059-1311
Funders:	Medical Research Council
Date of First Compliant Deposit:	14 November 2017
Date of Acceptance:	12 October 2017
Last Modified:	04 May 2023 22:07
URI:	https://orca.cardiff.ac.uk/id/eprint/106480

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