Johns Hopkins Medicine and OpenEvidence are joining forces to develop AI tools that integrate the best available medical evidence with individual patient histories and Johns Hopkins' clinical best practices — all while keeping the clinician firmly in the driver's seat. The partnership, described as at minimum an R&D and product collaboration, will focus on identifying high-impact clinical use cases and embedding AI naturally into existing workflows, with rigorous evaluation of outcomes along the way.

Beyond the clinic, the two organizations see a pressing need to rethink medical education itself. Johns Hopkins — the institution credited with defining 20th-century medical training — wants to shape what physician education looks like in the AI era, emphasizing core competencies like clinical reasoning, pathophysiology, and patient communication, while using AI to personalize learning and shift from a time-based to a competency-based training model.

Key Takeaways:

• Over 1.12 million licensed U.S. clinicians already use OpenEvidence, which recently hit a $15B valuation after a $250M funding round
• The partnership will explore AI integration into EHRs and clinical decision support, building on OpenEvidence's existing ties with Mount Sinai, Cedars-Sinai, Penn Medicine, and others
• A key concern driving the collaboration: preventing "cognitive offloading," where physicians over-rely on AI and exit training without mastering essential skills

Why it matters: As AI tools proliferate in healthcare at a rapid pace, partnerships like this one could set the standard for how medicine is both practiced and taught — making it critical to get the guardrails right from the start.