Accepted for/Published in: JMIR Formative Research
Date Submitted: Aug 26, 2025
Date Accepted: Jan 9, 2026
Web-based real-world statistics for better informed drug selection in epilepsy: survey and group interviews of physician perspectives.
ABSTRACT
Background:
Lately, big data studies have shown promise in using patient characteristics to rank antiseizure medications in epilepsy in terms of likelihood of success. How such results integrate into clinical practice has yet to be studied. We developed EPstat, a non-commercial tool that provides physicians with real-world treatment retention data from 33,998 epilepsy patients.
Objective:
This study investigates the user experience of EPstat after its pilot launch.
Methods:
An online questionnaire was distributed to physicians in our health service region’s neurology clinics (five hospitals). Descriptive statistics and thematic analysis were used to summarise responses. Additionally, three semi-structured workshops with neurologists and residents gathered further feedback.
Results:
Of the 27 respondents, 70% (n=19) were aware of EPstat, and 37% (n=10) had used it. Users rated EPstat highly for ease of use (median 5, IQR: 4–5) and applicability in clinical practice (median 4, IQR: 4–4). Two respondents (20%) indicated that the platform had influenced their choice of antiseizure medication. Workshop participants advocated expanding the platform to include retention data on subsequent antiseizure medications and general information relevant to epilepsy management.
Conclusions:
The notion of using big data to improve antiseizure medication selection has been well-received. However, there have been barriers to the initial use, and users request a more comprehensive resource that also incorporates other information related to epilepsy. Clinical Trial: Na
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