Physician Perspectives on Web-Based Real-World Statistics for Better-Informed Drug Selection in Epilepsy: Mixed...

Area of Science:

• Epilepsy research
• Health informatics
• Big data analytics in medicine

Background:

• Big data studies are emerging for ranking antiseizure medication (ASM) retention likelihood.
• Integrating these findings into clinical practice remains a challenge.
• EPstat was developed as a noncommercial tool to provide real-world ASM retention data for physicians treating epilepsy.

Purpose of the Study:

• To investigate the user experience of the EPstat tool after its initial pilot launch.
• To gather physician feedback on the utility and potential improvements for EPstat.

Main Methods:

• EPstat was developed iteratively and launched via email and information meetings.
• An online questionnaire and semistructured workshops/interviews with neurologists were used for feedback.
• Descriptive statistics and thematic analysis were applied to summarize responses.

Main Results:

• 70% of physicians were aware of EPstat, and 37% had used it.
• Users reported high ease of use (median 5) and clinical applicability (median 4).
• Two users indicated EPstat influenced their ASM choice; workshop participants requested data on newer ASMs.

Conclusions:

• The concept of using big data for ASM selection is well-received, despite initial usage barriers.
• Physicians desire a more comprehensive resource including newer ASMs and general epilepsy management information.
• Future updates and strategies like mobile access and guideline integration are proposed to increase EPstat's use and impact.