{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:07:16Z","timestamp":1782846436506,"version":"3.54.5"},"reference-count":17,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Form Res"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Lately, big data studies have shown promise in using patient characteristics to rank the likelihood of retention of antiseizure medications (ASMs), a measure indicating tolerability as well as effect. How such results can be integrated into clinical practice has yet to be studied. We developed EPstat, a noncommercial tool that provides physicians with real-world treatment retention data from 33,998 patients with epilepsy.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n This study investigated the user experience of EPstat after its pilot launch.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n EPstat was developed in an iterative process with first a prototype and then a final version accessible on the health care region intranet. EPstat was launched in 2022 through emails and information meetings at neurology departments. After 1 year, an online questionnaire was distributed to physicians in our health service region\u2019s neurology clinics (5 hospitals). Descriptive statistics and thematic analysis were used to summarize responses. To supplement the survey, 3 semistructured workshops or group interviews with neurologists and residents were used to gather further feedback.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n Of the 27 survey respondents, 19 (70%) were aware of EPstat and 10 (37%) had used it. Users rated EPstat highly for ease of use (median 5, IQR 4\u20105) and applicability in clinical practice (median 4, IQR 4\u20104). Two of the 10 respondents who had used it indicated that the platform had influenced their choice of ASM. Workshop participants advocated for expanding the platform to include retention data on newer ASMs and general information relevant to epilepsy management.<\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n The notion of using big data to improve ASM selection was well received. However, there were barriers to the initial use, and users requested a more comprehensive resource that also incorporated other information related to epilepsy. EPstat is now being updated with more recent ASM statistics, including information on newer ASMs. Mobile access, more information for physicians, and mentioning the tool in regional guidelines are some possible measures to increase use. Linking multinational statistics could also increase the precision of the presented data and, thus, increase usefulness. Study of EPstat will continue and should include thematic analysis of representative and rigorously sampled workshop participants. Such studies are also likely to provide information on how physicians and health services receive web-based tools, which are likely to soon be driven by artificial intelligence. In similar projects, we recommend greater participatory involvement of both health care providers and patients already at the design stage.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/82958","type":"journal-article","created":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T19:50:57Z","timestamp":1770839457000},"page":"e82958-e82958","source":"Crossref","is-referenced-by-count":0,"title":["Physician Perspectives on Web-Based Real-World Statistics for Better-Informed Drug Selection in Epilepsy: Mixed Methods 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