OpenEvidence brings clinical search directly into NYU Langone Epic EHR

A physician at an NYU Langone outpatient clinic seeking the latest treatment guidelines for a complex patient case has historically faced a clumsy choice: look away from the patient, unlock a personal smartphone, and query an unvetted web browser. Under a new partnership, that information flows directly into the clinical workstation.

NYU Langone Health is integrating OpenEvidence into its Epic electronic health record workflow. Through a collaboration announced by the partners, the technology embeds directly into the EHR system, using a feature they call Patient Aware Clinical Intelligence. This integration allows healthcare providers to ask natural-language clinical questions and receive answers grounded in medical literature, complete with patient context, all without leaving the active chart.

The deployment represents an expansion of clinical artificial intelligence within one of the largest academic medical centers in the United States. It moves clinical generative search from a decentralized tool used on individual mobile devices to an enterprise-approved utility operating at scale.

The scale of the integration spans the entirety of the NYU Langone clinical network. According to the health system, its facilities handle millions of outpatient visits and hundreds of thousands of emergency department visits annually across multiple inpatient locations and hundreds of outpatient clinics.

Additionally, the deployment covers family health centers, which support hundreds of thousands of annual visits, as well as medical trainees at both the NYU Grossman School of Medicine and the NYU Grossman Long Island School of Medicine.

By embedding the software directly into the Epic EHR, the institution is ensuring that both experienced clinicians and medical students have uniform access to literature-grounded answers. This systematic deployment reflects a growing trend among academic medical systems to institutionalize digital search tools rather than leaving their adoption to individual discretion.

Embedding literature into the workflow

The core of the technology is Patient Aware Clinical Intelligence. Led by NYU Langone chief digital and information officer Nader Mherabi and OpenEvidence chief executive Daniel Nadler, the collaboration aims to streamline clinical decision support.

Rather than performing generic literature searches, clinicians can query the system using natural language. The tool reads the query, references current medical literature, and formats an answer that accounts for the specific clinical context of the patient whose chart is open. This capability eliminates the need to manually copy patient details into a separate search interface, reducing cognitive friction during patient encounters.

By keeping clinicians within the Epic environment, the tool seeks to minimize workflow interruptions. The clinical team can access literature-guided evidence while maintaining focus on the patient, bringing relevant medical research directly to the point of care.

Moving beyond the phone screen

The expansion at NYU Langone marks a broadening of OpenEvidence's presence in the New York metropolitan area, where it already has deployments at NewYork-Presbyterian and Mount Sinai.

The adoption of clinical search tools is supported by broader industry trends. A study published in JAMA analyzed clinician search behavior, logging millions of queries from hundreds of thousands of clinicians in the United States.

Although the scale of the JAMA study was broad, the researchers focused entirely on measuring clinician usage patterns. They did not evaluate the clinical accuracy of the answers provided by these search engines, nor did they study the subsequent patient outcomes resulting from these queries. This volume of queries demonstrates that clinicians are already actively seeking digital answers during their daily routines, and the challenge for healthcare organizations is transitioning these unstructured queries into a secure, integrated, and governed environment.

As clinical search transitions from an ad hoc tool to an enterprise utility, the dynamics of healthcare technology procurement are changing. Clinical search is no longer just a free application that clinicians download on their mobile phones; it has become an enterprise-sanctioned software layer running inside the electronic health record.

This transition shifts the purchasing authority from individual doctors to the chief information officer. When a tool is integrated directly into the electronic health record of a health system, the primary questions evolve. It is no longer enough to ask whether clinicians enjoy using the tool. Instead, clinical and technology leaders must determine who is auditing patient-context answers at an institutional scale.

For healthcare organizations, logging, governance, and clinical outcome measurement will likely become the primary requirements for future technology procurement. Clinical leaders will need to ensure that the answers provided by AI search tools are accurate, safe, and aligned with institutional standards, moving beyond simple usage statistics to rigorous clinical oversight.