Intermountain Invests in Layer Health Data Abstraction Platform
In March I had the opportunity to interview David Sontag, Ph.D., a professor at MIT and co-founder and CEO of a Boston-based startup company called Layer Health, which has developed a large language model (LLM)-powered data abstraction platform to extract clinical data from patient medical charts for data registries, clinical research and care optimization.
In our interview, Sontag discussed early partnerships with the American Cancer Society and Froedtert and Wisconsin Medical College. Now the company has announced a collaboration with Utah-based Intermountain Health that includes a strategic investment from Intermountain Ventures, the health system’s innovation and venture capital arm, as well as a multi-year initiative to deploy the Layer Health AI platform across multiple clinical registries to improve accuracy, efficiency and scalability of clinical data abstraction.
Intermountain said its Clinical Data Management team will first work with Layer Health to validate the AI’s ability to achieve high accuracy prior to deployment, ensuring the AI meets clinical performance standards required to support real-world clinical registry reporting. Starting with registries in stroke, bariatric surgery and cardiovascular disease, Intermountain Health will deploy Layer Health’s AI platform across Intermountain’s full network, spanning 33 hospitals and multiple states, with plans to expand to other registry areas in the future.
"Layer Health’s technology represents a meaningful step forward,” said Nickolas Mark, managing partner of Intermountain Ventures, in a statement. “We’re excited to partner with a company whose AI expertise and commitment to validation align with our broader vision for using innovation to solve complex operational challenges in healthcare."
Built to automate the labor-intensive process of medical chart review, the Layer Health platform supports functions such as quality reporting, registry submission, and a growing range of operational and clinical workflows. Leveraging advanced large language models trained on rich, longitudinal patient data, the platform can interpret both structured and unstructured clinical information with high accuracy, the company said.
“Layer Health’s technology reflects the kind of AI solution that will drive meaningful change for our system,” said Cara Camiolo Reddy, M.D., chief quality and safety officer at Intermountain Health, in a statement. “Our team manages more than 35 active registries and is constantly evaluating how to support more registries that demonstrate our clinical excellence. Layer offers a scalable approach that allows us to support existing registries more efficiently and finally move forward with new ones. Furthermore, with the support of AI, our team can focus more on driving meaningful improvements in patient care.”
While the initial focus is on clinical registry data abstraction, both organizations said they recognize the potential for Layer Health’s platform to support other high-value chart review use cases in the future.
