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Validating epilepsy diagnoses in routinely collected data / Beata Fonferko-Shadrach; Arron S. Lacey; Catharine P. White; H.W. Rob Powell; Inder M.S. Sawhney; Ronan A. Lyons; Phil E.M. Smith; Mike P. Kerr; Mark I. Rees; W. Owen Pickrell

Seizure, Volume: 52, Pages: 195 - 198

Swansea University Author: Pickrell, Owen

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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 Link...

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Published in: Seizure
ISSN: 10591311
Published: 2017
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa36207
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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 antiepileptic 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 Description: We acknowledge the support from the Farr Institute @ CIPHER. The Farr Institute @ CIPHER is supported by a 10-funder consortium: Arthritis Research UK, the British Heart Foundation, Cancer Research UK, the Economic and Social Research Council, the Engineering and Physical Sciences Research Council, the Medical Research Council, the National Institute of Health Research, the Health and Care Research Wales (Welsh Assembly Government), the Chief Scientist Office (Scottish Government Health Directorates), the Wellcome Trust, (MRC Grant No: MR/K006525/1). We also acknowledge support from the Brain Repair and Intracranial Neurotherapeutics (BRAIN) Unit which is funded by Health and Care Research Wales.
Keywords: Diagnosis, validation, routinely collected data, epilepsy
College: Swansea University Medical School
Start Page: 195
End Page: 198