Digital Therapeutics (DTx) for low back pain

Brim Analytics is driving to the next cure, faster with a democratized AI-guided chart abstraction system. Chart abstraction is the process of converting unstructured clinical notes into structured data, an essential task across healthcare, including clinical trial matching, academic research, registries for cancer and heart disease, and many more. Brim is an AI-guided tool for chart abstraction that prioritizes privacy and security, creates traceability of data, and is dramatically faster than human curators alone.

Faster, smarter chart abstraction to streamline clinical workflows, pre-screen clinical trials, accelerate retrospective research, and more.

- Clinical Evidence: SelfBack has conducted a large scale (n=461) multi site RCT study

- Use of AI: Selfback uses AI to generate personalize self-management plansfor each new user, unlike all other apps in this category

Brim enables fast and flexible abstraction of structured data from unstructured notes.

• Fast Abstraction. AI-guided generation saves 80% of the time relative to manual abstraction with comparable accuracy.
• Scalable. Abstract data at scale, rather than note-by-note.
• Flexible. Easily iterate on the fields you derive as you learn or your process evolves.
• EHR-agnostic. Import and export via a standard format.

• Privacy and Security first. Brim is fully secure, and we do not train on your data. You can implement in your institution's cloud environment, or in a single-tenant deployment. Leverage your institution's LLM endpoint. Brim supports Open AI, Azure Open AI, Bedrock, and other LLMs to get the newest foundational models without adding another vendor.
• Built for researchers and abstractors. Purpose-built interface for abstraction helps humans move faster and improves the accuracy of abstracted data.
• Domain flexibility. Brim has been used for projects in cancer research, clinical trials, orthopedic injuries, and many more. Brim optimizes variables for your project based on your feedback, improving abstraction in real time.