The news: Anthropic expanded into healthcare with the debut of Claude for Healthcare for doctors, consumers, and hospital systems.

• For clinician and administrator answers, Claude’s health sources include PubMed, the latest International Classification of Diseases (ICD-10), and CMS’ coverage database.
• Clinicians at Banner Health hospital system are already using Claude; 85% reported faster work with higher accuracy, per Anthropic. Other customers include Stanford Health Care and Elation Health.

Anthropic also expanded Claude for Life Sciences, launched in October for biopharma scientists and researchers with connections to Medidata, ClinicalTrials.gov, and the ToolUniverse library of scientific tools. US consumers with Claude Pro and Max subscriptions can upload lab results and health records.

Why it matters: Anthropic’s move intensifies the race among AI platforms targeting medical professionals and consumers, days after OpenAI launched ChatGPT for Healthcare for medical professionals and ChatGPT for Health for consumers.

For healthcare providers, the crowded space already includes medical-focused players like OpenEvidence and Abridge.

• Among AI tools used by physicians, 45% use OpenEvidence (a AI medical-specific search for physicians), and 15.6% use ChatGPT. Another 5% use Abridge (an AI medical scribe), and 3% use Claude, per a recent OffCall survey of 1,000 physicians published in December. Both ChatGPT and Claude are used more for general purposes.
• More than 100 million Americans were treated by a doctor who used OpenEvidence in 2025, CEO Daniel Nadler said at JPM this week, per STAT. He added that the platform last year grew from 2.6 million queries per month to almost 18 million in December 2025.

Implications for healthcare providers and healthcare systems: As AI tools for medical professionals flood the market, providers and health systems will be pushed to choose platforms. While physicians may gravitate toward tools they already trust or use independently, health systems will look to vendors that can integrate cleanly into workflows, meet compliance requirements, and demonstrate consistent accuracy at scale.

Competition will shift from general-purpose capabilities to specialization, locked-in partnerships, and proof of clinical value, leading AI vendors to build niches or specialities in areas like documentation or diagnostics support. As with the emerging consumer health AI battle, ease of use will be table stakes, while differentiation comes from speed, trusted data sources, and the ability to support clinical decision-making without adding risk or friction.