ArticleEpilepsy research2020
Accuracy of ICD-10-CM claims-based definitions for epilepsy and seizure type.
Article in Epilepsy research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
29 citing papers in PubMed, 42 citations in OpenAlex.
- Identification of patients with epilepsy using automated electronic health records phenotyping.Epilepsia · 2023Trial
- Polypharmacy burden and incident epilepsy among older adults in the United States.Epilepsia open · 2026Article
- Levetiracetam for Seizure Prophylaxis after Traumatic Brain Injury: A Severity-Stratified Cohort Study of 51,000 Patients.Annals of neurology · 2026Article
- Article
- Sodium-glucose cotransporter 2 inhibitors and the risk of late onset epilepsy: A real-world cohort study.Epilepsia · 2026Article
- Comparing three natural language processing methods for the automatic identification of epilepsy patients from French clinical notes.Epilepsia · 2026Article
- Vitamin D deficiency and long-term risk of epilepsy or seizure in type 2 diabetes: a multicenter real-world cohort study.Frontiers in nutrition · 2026Article
- Development and Validation of an Administrative Algorithm to Identify Veterans With Epilepsy.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2026Article
- Risk of neurological and psychiatric diagnoses in COVID-19 survivors: A multicenter retrospective cohort study using electronic health records.World journal of psychiatry · 2025Article
- Article
- Article
- Article
- Extracting epilepsy-related information from unstructured clinic letters using large language models.Epilepsia · 2025Article
- A multidisciplinary look into transgender and gender diverse people with epilepsy: An at-risk and underreported population.Epilepsia · 2025Article
- Article
- Polygenic Risk of Epilepsy and Poststroke Epilepsy.Stroke · 2024Article
- Incident Epilepsy Among US Medicare Beneficiaries, 2019: Differences by Age, Sex, and Race/Ethnicity.Neurology · 2024Article
- Excess prevalence of preexisting chronic conditions in older adults with incident epilepsy.Epilepsia · 2024Article
- Characterizing emergency department and inpatient health care utilization after seizure-related hospitalization: A retrospective cohort study.Epilepsia · 2024Article
- Use of Healthcare Claims Data to Generate Real-World Evidence on Patients With Drug-Resistant Epilepsy: Practical Considerations for Research.Journal of health economics and outcomes research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
Abstract
objectiveTo evaluate the accuracy of ICD-10-CM claims-based definitions for epilepsy and classifying seizure types in the outpatient setting.
methodsWe reviewed electronic health records (EHR) for a cohort of adults aged 18+ years seen by six neurologists who had an outpatient visit at a level 4 epilepsy center between 01/2019-09/2019. The neurologists used a standardized documentation template to capture the diagnosis of epilepsy (yes/no/unsure), seizure type (focal/generalized/unknown), and seizure frequency in the EHR. Using linked ICD-10-CM codes assigned by the provider, we assessed the accuracy of claims-based definitions for epilepsy, focal seizure type, and generalized seizure type against the reference-standard EHR documentation by estimating sensitivity (Sn), specificity (Sp), positive predictive value (PPV), and negative predictive value (NPV).
resultsThere were 673 eligible outpatient encounters. After review of EHRs for standardized documentation, an analytic sample consisted of 520 encounters representing 402 unique patients. In the EHR documentation, 93.5 % (n = 486/520) of encounters were with patients with a diagnosis of epilepsy. Of those, 66.0 % (n = 321/486) had ≥1 focal seizure, 41.6 % (n = 202/486) had ≥1 generalized seizure, and 7% (n = 34/486) had ≥1 unknown seizure. An ICD-10-CM definition for epilepsy (i.e., ICD-10 G40.X) achieved Sn = 84.4 % (95 % CI 80.8-87.5%), Sp = 79.4 % (95 % CI 62.1-91.3%), PPV = 98.3 % (95 % CI 96.6-99.3%), and NPV = 26.2 % (95 % CI 18.0-35.8%). The classification of focal vs generalized/unknown seizures achieved Sn = 69.8 % (95 % CI 64.4-74.8%), Sp = 79.4 % (95 % CI 72.4-85.3%), PPV = 86.8 % (95 % CI 82.1-90.7%), and NPV = 57.5 % (95 % CI 50.8-64.0%).
conclusionsClaims-based definitions using groups of ICD-10-CM codes assigned by neurologists in routine outpatient clinic visits at a level 4 epilepsy center performed well in discriminating between patients with and without a diagnosis of epilepsy and between seizure types.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.