Patient characteristics and antiseizure medication pathways in newly diagnosed epilepsy: Feasibility and pilot results using the common data model in a single-center electronic medical record database.

Antiseizure medication Epilepsy Observational Health Data Science and Informatics (OHDSI) Observational Medical Outcomes Partnership (OMOP) Practice patterns

Journal

Epilepsy & behavior : E&B
ISSN: 1525-5069
Titre abrégé: Epilepsy Behav
Pays: United States
ID NLM: 100892858

Informations de publication

Date de publication:
04 2022
Historique:
received: 22 11 2021
revised: 28 01 2022
accepted: 14 02 2022
pubmed: 12 3 2022
medline: 6 4 2022
entrez: 11 3 2022
Statut: ppublish

Résumé

Efforts to characterize variability in epilepsy treatment pathways are limited by the large number of possible antiseizure medication (ASM) regimens and sequences, heterogeneity of patients, and challenges of measuring confounding variables and outcomes across institutions. The Observational Health Data Science and Informatics (OHDSI) collaborative is an international data network representing over 1 billion patient records using common data standards. However, few studies have applied OHDSI's Common Data Model (CDM) to the population with epilepsy and none have validated relevant concepts. The goals of this study were to demonstrate the feasibility of characterizing adult patients with epilepsy and ASM treatment pathways using the CDM in an electronic health record (EHR)-derived database. We validated a phenotype algorithm for epilepsy in adults using the CDM in an EHR-derived database (2001-2020) against source records and a prospectively maintained database of patients with confirmed epilepsy. We obtained the frequency of all antecedent conditions and procedures for patients meeting the epilepsy phenotype criteria and characterized ASM exposure sequences over time and by age and sex. The phenotype algorithm identified epilepsy with 73.0-85.0% positive predictive value and 86.3% sensitivity. Many patients had neurologic conditions and diagnoses antecedent to meeting epilepsy criteria. Levetiracetam incrementally replaced phenytoin as the most common first-line agent, but significant heterogeneity remained, particularly in second-line and subsequent agents. Drug sequences included up to 8 unique ingredients and a total of 1,235 unique pathways were observed. Despite the availability of additional ASMs in the last 2 decades and accumulated guidelines and evidence, ASM use varies significantly in practice, particularly for second-line and subsequent agents. Multi-center OHDSI studies have the potential to better characterize the full extent of variability and support observational comparative effectiveness research, but additional work is needed to validate covariates and outcomes.

Identifiants

pubmed: 35276502
pii: S1525-5050(22)00079-8
doi: 10.1016/j.yebeh.2022.108630
pii:
doi:

Substances chimiques

Levetiracetam 44YRR34555

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

108630

Subventions

Organisme : NCATS NIH HHS
ID : KL2 TR001874
Pays : United States

Informations de copyright

Copyright © 2022 Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Matthew Spotnitz (M)

Department of Biomedical Informatics, Columbia University Irving Medical Center, United States.

Anna Ostropolets (A)

Department of Biomedical Informatics, Columbia University Irving Medical Center, United States.

Victor G Castano (VG)

Department of Neurological Surgery, Columbia University Irving Medical Center, United States.

Karthik Natarajan (K)

Department of Biomedical Informatics, Columbia University Irving Medical Center, United States.

Genna J Waldman (GJ)

Department of Neurology, Columbia University Irving Medical Center, United States.

Michael Argenziano (M)

Department of Neurological Surgery, Columbia University Irving Medical Center, United States.

Ruth Ottman (R)

Department of Neurology, Columbia University Irving Medical Center, United States; The Gertrude H. Sergievsky Center, Columbia University Vagelos College of Physicians and Surgeons, United States; Department of Epidemiology, Mailman School of Public Health, Columbia University Irving Medical Center, United States; Division of Translational Epidemiology, New York State Psychiatric Institute, United States.

George Hripcsak (G)

Department of Biomedical Informatics, Columbia University Irving Medical Center, United States.

Hyunmi Choi (H)

Department of Neurology, Columbia University Irving Medical Center, United States.

Brett E Youngerman (BE)

Department of Neurological Surgery, Columbia University Irving Medical Center, United States. Electronic address: bey2103@cumc.columbia.edu.

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