The healthcare AI momentum isn’t showing any signs of letting up, and chart review automation startup Layer Health just added another $21M to the segment’s quickly growing venture total.
Layer’s AI platform leverages LLMs trained on longitudinal patient data to automate data abstraction for the medical chart reviews that underpin a wide range of clinical and administrative workflows, including:
- Quality Reporting & Clinical Registries – extracting data from clinical registries and quality measurement programs to improve accuracy and ensure compliance
- Hospital Operations & Revenue Cycle – enhancing clinical documentation integrity and coding processes to optimize reimbursement and reduce denials
- Clinical Decision-Making & Patient Care – providing physicians with real-time insights that synthesize a patient’s full medical history to support personalized treatments
- Clinical Research & Real-World Data – accelerating patient cohort identification for research studies and improving real-world evidence generation
Chart review has been a longstanding challenge for most health systems, which can spend upwards of $6M per hospital on personnel costs for care quality data reporting.
- At the same time, this data represents an invaluable resource for unifying care data with clinical and financial outcomes, enabling treatment decisions to be mapped to their real-world impact.
Flare Capital Partners’ investment memo for Layer laid out how the clinical registries that map chart information to direct outcomes have historically been hamstrung by their unstructured source data.
- Abstracting this data into a usable format is a time-consuming manual process, and most technological fixes have usually only involved automating small parts of it.
- By combining the reasoning ability of large language models with the cost-efficiency of small language models, Flare believes that Layer can capture a major slice of the multi-billion dollar care quality reporting market (plus another chunk of the life sciences sector’s growing appetite for real-world data).
The Takeaway
Surfacing insights from medical charts requires peeling back countless layers of structured and unstructured data, which makes it particularly well-suited for both AI solutions and ambitious startups like Layer that are bringing them to market.
