OpenEvidence Gains Wide Adoption Among U.S. Doctors

OpenEvidence, an AI-powered medical search and chatbot tool, was used by about 65% of U.S. doctors across almost 27 million clinical encounters in April, the company told NBC News. Per NBC News, OpenEvidence representatives said roughly 650,000 U.S. physicians actively use the product and another 1.2 million users are international. NBC interviewed more than two dozen clinicians, administrators and researchers and reported clinicians use the tool for clinical decision-making, preparing licensing-exam study materials and drafting documentation. NBC also reported that clinicians told the outlet the tool sometimes "occasionally flubbed or exaggerated its answers, particularly on rare conditions or in 'edge' cases," and that portions of the free service are supported by advertising, often from pharmaceutical and medical device companies.

Editorial analysis - technical context: Public reporting focuses on OpenEvidence as a search/chat interface that returns long, citation-rich responses, which clinicians in NBC's reporting described using as a rapid consult or study aid. NBC's dataset referenced by Dr. Anupam Jena includes roughly 90 million queries submitted since 2024, according to Jena, a co-researcher cited in NBC's coverage. Reporting by Gizmodo summarizes investor backing and company profile, noting OpenEvidence is headquartered in Miami and has attracted venture capital from firms including Sequoia Capital, Andreessen Horowitz, Google Ventures, Thrive Capital and Nvidia, per Gizmodo.

Industry context: Rapid clinician adoption of a single, free AI tool creates several practice-level and ecosystem-level implications. High-use tools that combine natural-language synthesis with external citations can accelerate information retrieval and documentation workflows in time-pressured clinical settings. At the same time, the NBC reporting highlights accuracy concerns on low-prevalence or edge-case conditions, and Gizmodo and NBC both note the product's ad-supported elements, with ads reportedly coming from pharmaceutical and device companies. For practitioners building or evaluating clinical AI, those two characteristics, broad adoption plus commercial advertising in the product, are important signals for model evaluation, citation provenance, and potential commercial influence on surfaced results.

Observers should follow independent validation studies of OpenEvidence's outputs on common and rare conditions, third-party audits of citation provenance and hallucination rates, and any disclosures about advertiser relationships and ad targeting inside clinical workflows. Researchers and hospital IT teams will likely monitor how often clinicians follow the tool's citations into primary literature versus using the tool's synthesis directly in patient care, a usage pattern NBC asked clinicians about in its reporting. Finally, adoption metrics and investor signals reported by Gizmodo can be cross-checked against regulatory filings or published transparency reports if the company issues them.