Literature DB >> 32474909

The accuracy of using administrative healthcare data to identify epilepsy cases: A systematic review of validation studies.

Gashirai K Mbizvo1, Kyle H Bennett1, Christian Schnier2, Colin R Simpson2,3, Susan E Duncan1,4, Richard F M Chin1,5.   

Abstract

Our objective was to undertake a systematic review ascertaining the accuracy of using administrative healthcare data to identify epilepsy cases. We searched MEDLINE and Embase from 01/01/1975 to 03/07/2018 for studies evaluating the diagnostic accuracy of routinely collected healthcare data in identifying epilepsy cases. Any disease coding system in use since the International Classification of Diseases, Ninth Revision (ICD-9) was permissible. Two authors independently screened studies, extracted data, and quality-assessed studies. We assessed positive predictive value (PPV), sensitivity, negative predictive value (NPV), and specificity. The primary analysis was a narrative synthesis of review findings. Thirty studies were included, published between 1989 and 2018. Risks of bias were low, high, and unclear in 4, 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% (USA), 47.0%-100% (UK), and 37.0%-88.0% (Norway). Sensitivities included ranges of 22.2%-99.7% (Canada), 12.2%-97.3% (USA), and 79.0%-94.0% (UK). Nineteen studies contained at least one algorithm with a PPV >80%. Sixteen studies contained at least one algorithm with a sensitivity >80%. PPV was highest in algorithms consisting of disease codes (ICD-10 G40-41, ICD-9 345) in combination with one or more AEDs. 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 one or more AEDs. Although using AEDs alone achieved high sensitivities, the associated PPVs were low. Most NPVs and specificities were >90%. We conclude that it is reasonable to use administrative data to identify people with epilepsy (PWE) in epidemiological research. Studies prioritizing high PPVs should focus on combining disease codes with AEDs. Studies prioritizing high sensitivities should focus on combining symptom codes with AEDs. We caution against the use of AEDs alone to identify PWE.
© 2020 The Authors. Epilepsia published by Wiley Periodicals LLC on behalf of International League Against Epilepsy.

Entities:  

Keywords:  diagnostic test accuracy; international classification of diseases; positive predictive value; routine data; seizures; sensitivity

Year:  2020        PMID: 32474909     DOI: 10.1111/epi.16547

Source DB:  PubMed          Journal:  Epilepsia        ISSN: 0013-9580            Impact factor:   5.864


  7 in total

1.  Validation of Pediatric Idiopathic Generalized Epilepsy Diagnoses from the Danish National Patient Register During 1994‒2019.

Authors:  Magnus Spangsberg Boesen; Melita Cacic Hribljan; Søren Kirchhoff Christensen; Amalie Wandel Klein-Petersen; Sahla El Mahdaoui; Malini Vendela Sagar; Emilie Schou; Anna Korsgaard Eltvedt; Malene Landbo Børresen; Maria Jose Miranda; Alfred Peter Born; Peter Vilhelm Uldall; Lau Caspar Thygesen
Journal:  Clin Epidemiol       Date:  2022-04-19       Impact factor: 5.814

2.  Cognitive disorders in childhood epilepsy: a comparative longitudinal study using administrative healthcare data.

Authors:  Anna-Lisa Sorg; Rüdiger von Kries; Ingo Borggraefe
Journal:  J Neurol       Date:  2022-02-15       Impact factor: 6.682

3.  Response to Frequency of new seizures after SARS-CoV-2 infections may depend on the length of follow-up.

Authors:  Gabriel Westman; Johan Zelano
Journal:  Seizure       Date:  2022-08-20       Impact factor: 3.414

4.  Antiseizure medication treatment pathways for US Medicare beneficiaries with newly treated epilepsy.

Authors:  Samuel W Terman; Brett E Youngerman; Hyunmi Choi; James F Burke
Journal:  Epilepsia       Date:  2022-03-25       Impact factor: 6.740

5.  Incidence of and predictors for antiseizure medication gaps in Medicare beneficiaries with epilepsy: a retrospective cohort study.

Authors:  Samuel W Terman; Joshua D Niznik; Geertruida Slinger; Willem M Otte; Kees P J Braun; Carole E Aubert; Wesley T Kerr; Cynthia M Boyd; James F Burke
Journal:  BMC Neurol       Date:  2022-09-01       Impact factor: 2.903

6.  Psychiatric comorbidities and all-cause mortality in epilepsy: A nationwide cohort study.

Authors:  Kristijonas Puteikis; Edita Kazėnaitė; Rūta Mameniškienė
Journal:  Front Neurol       Date:  2022-08-18       Impact factor: 4.086

7.  Increasing Trends in the Incidence and Prevalence of Epilepsy in Korea.

Authors:  Ji Ye Jeon; Hyesung Lee; Ju Young Shin; Hye Jin Moon; Seo Young Lee; Jae Moon Kim
Journal:  J Clin Neurol       Date:  2021-07       Impact factor: 3.077

  7 in total

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