Teams across disciplines and institutions at Johns Hopkins Medicine are working together to connect exceptional patient care with bold scientific discovery, continuous learning and new approaches to innovation. A critical opportunity lies in something we already possess in abundance: clinical data generated through the care of millions of patients.

 Our goal is to unlock this information as a resource for discovery to help in answering some of medicine’s most pressing questions: Why do certain diseases progress rapidly in some patients but not others? How we can detect disease earlier? How can we tailor treatments more precisely for individuals while improving consistency across various populations? One of the most promising tools enabling this work is REACH: the Research Enclave for Analyzing Clinical Health Data.

REACH provides Johns Hopkins researchers with access to a de-identified version of our electronic medical record data, unlocking the power of clinical information while safeguarding privacy. Its scale is extraordinary: over 1 billion structured data points and 190 million clinical notes across more than 8 million patients. Soon, we will also add de-identified radiology data — an additional 24 million studies. Pathology, followed by genomic and molecular data, will be next. Over time, this will create a truly multimodal research resource capable of revealing clinical patterns more quickly and efficiently than ever before.

What makes this opportunity especially powerful for Johns Hopkins Medicine is our unique combination of scale and expertise. Many peer institutions maintain large datasets but lack the research depth to fully leverage them. Others have world-class research capacity but don’t operate expansive health systems where innovation can be deployed in real time. At Johns Hopkins, we have both, allowing experts in medicine, public health, nursing, engineering, business and beyond to collaborate and innovate together around leading clinical challenges and move more rapidly from discovery to implementation.

Collaboration beyond our enterprise will further amplify this work. For example, Johns Hopkins is part of the Cancer AI Alliance, a network of leading cancer centers and industry partners that is building a first-of-its-kind data platform powered by “federated learning.”

This allows each institution to retain its data securely behind its own firewalls while AI models are shared and trained across sites. Federated learning enables collective learning while maintaining strong data protections — an advantage that is especially valuable when studying rare conditions, where larger, combined datasets lead to more meaningful insights.

Together, these efforts position Johns Hopkins to be at the forefront of tackling the next great waves of disease: cancer, neurologic diseases, cardiac and cardiovascular diseases, and conditions associated with aging. By integrating comprehensive clinical data with advances in artificial intelligence and precision medicine, we can accelerate progress toward a health system that anticipates health risk, intervenes sooner and reduces unnecessary variation in care.

REACH is a critical building block in this effort. It will help fuel discovery, enhance training for the next generation of scientists and clinicians and translate findings into meaningful improvements in care delivery.

The future of medicine will belong firmly to institutions that continuously learn from their own data and act on that knowledge. With tools like REACH, Johns Hopkins Medicine will not simply keep pace — we will help shape that future.