{"id":2838,"date":"2026-08-06T17:00:08","date_gmt":"2026-08-06T17:00:08","guid":{"rendered":"https:\/\/blogs.chapman.edu\/pharmacy\/?p=2838"},"modified":"2026-08-06T23:33:43","modified_gmt":"2026-08-06T23:33:43","slug":"dr-sherry-wangs-research-raises-questions-about-a-widely-used-opioid-risk-tool","status":"publish","type":"post","link":"https:\/\/blogs.chapman.edu\/pharmacy\/2026\/08\/06\/dr-sherry-wangs-research-raises-questions-about-a-widely-used-opioid-risk-tool\/","title":{"rendered":"Dr. Sherry Wang&#8217;s Research Raises Questions About a Widely Used Opioid Risk Tool"},"content":{"rendered":"<p><span data-contrast=\"none\">As AI becomes increasingly involved in healthcare decisions,<\/span><span data-ccp-props=\"{&quot;335557856&quot;:16777215,&quot;335559731&quot;:720,&quot;335559739&quot;:0}\">\u00a0<\/span><span data-contrast=\"none\">transparency and reliability are critical to its success.<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"wp-image-2839 alignright\" style=\"font-weight: inherit\" src=\"https:\/\/blogs.chapman.edu\/pharmacy\/wp-content\/uploads\/sites\/65\/2026\/08\/sherry-wang-1-279x300.jpg\" alt=\"Sherry Wang, Ph.D., MPhil, BSc\" width=\"173\" height=\"186\" srcset=\"https:\/\/blogs.chapman.edu\/pharmacy\/wp-content\/uploads\/sites\/65\/2026\/08\/sherry-wang-1-279x300.jpg 279w, https:\/\/blogs.chapman.edu\/pharmacy\/wp-content\/uploads\/sites\/65\/2026\/08\/sherry-wang-1-951x1024.jpg 951w, https:\/\/blogs.chapman.edu\/pharmacy\/wp-content\/uploads\/sites\/65\/2026\/08\/sherry-wang-1-768x827.jpg 768w, https:\/\/blogs.chapman.edu\/pharmacy\/wp-content\/uploads\/sites\/65\/2026\/08\/sherry-wang-1-1427x1536.jpg 1427w, https:\/\/blogs.chapman.edu\/pharmacy\/wp-content\/uploads\/sites\/65\/2026\/08\/sherry-wang-1-1902x2048.jpg 1902w\" sizes=\"auto, (max-width: 173px) 100vw, 173px\" \/><\/p>\n<p><span style=\"font-size: 16px\" data-contrast=\"none\">CUSP\u2019s <\/span><span style=\"font-size: 16px\" data-contrast=\"none\">Dr. Sherry <\/span><span style=\"font-size: 16px\" data-contrast=\"none\">Yun Wang, winner of Women in AI\u2019s 2025 Researcher of<\/span> <span style=\"font-size: 16px\" data-contrast=\"none\">the Year Award, continues to drive progress in this<\/span><span style=\"font-size: 16px\" data-contrast=\"none\"> space.\u00a0<\/span><span style=\"font-size: 16px\" data-contrast=\"none\">Wang has <\/span><span style=\"font-size: 16px\" data-contrast=\"none\">published <\/span><span style=\"font-size: 16px\" data-contrast=\"none\">research in leading journals including JAMA, The Lancet,\u00a0<\/span><span style=\"font-size: 16px\" data-contrast=\"none\">and<\/span><span style=\"font-size: 16px\" data-contrast=\"none\">\u00a0Neuroepidemiology.<\/span><span style=\"font-size: 16px\" data-ccp-props=\"{&quot;335557856&quot;:16777215,&quot;335559739&quot;:0}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"none\">Wang\u2019s most recent study found that\u00a0NarxCare, a proprietary opioid risk algorithm used in over 20 states, could not be independently reproduced using its own publicly disclosed methods.\u00a0npj\u00a0Digital Medicine, part of the Nature portfolio, published the finding. The journal has an impact factor of 18.0 and ranks #1 among 194 journals in Health Care Sciences &amp; Services. Wang\u2019s team\u00a0attempted\u00a0to recreate the algorithm&#8217;s functioning using\u00a0NarxCare\u2019s\u00a0own data alongside real-world data\u00a0sets, but\u00a0could not match its outputs.<\/span><span data-ccp-props=\"{&quot;335557856&quot;:16777215,&quot;335559731&quot;:720,&quot;335559739&quot;:0}\">\u00a0<\/span><\/p>\n<p><span data-ccp-props=\"{&quot;335557856&quot;:16777215,&quot;335559731&quot;:720,&quot;335559739&quot;:0}\">\u00a0<\/span><span data-contrast=\"none\">The results raise real questions about accountability for a tool that actively shapes medication decisions for patients across the country. Wang\u2019s research focuses\u00a0on developing trustworthy, interpretable healthcare AI systems using large-scale real-world data. At CUSP, her work reflects a broader commitment to holding healthcare AI to the same standard of rigor as the medicine it supports; a standard that makes clear why algorithms used to guide patient care need to be verifiable.<\/span><span data-ccp-props=\"{&quot;335557856&quot;:16777215,&quot;335559731&quot;:720,&quot;335559739&quot;:0}\">\u00a0<\/span><\/p>\n<p><a href=\"https:\/\/www.nature.com\/articles\/s41746-026-02491-y\"><span data-contrast=\"none\">Read the full study.<\/span><\/a><span data-ccp-props=\"{&quot;335557856&quot;:16777215,&quot;335559739&quot;:0}\">\u00a0<\/span><\/p>\n<p><em>This article was co-written by\u00a0<a href=\"https:\/\/www.linkedin.com\/in\/silas-fernandes-02bb3a215\/\" target=\"_blank\" rel=\"noopener noreferrer\">Silas Fernandes<\/a>.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>As AI becomes increasingly involved in healthcare decisions,\u00a0transparency and reliability are critical to its success. CUSP\u2019s Dr. Sherry Yun Wang, [&hellip;]<\/p>\n","protected":false},"author":5616,"featured_media":2844,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center 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