Medisolv provides an LLM‑based Clinical Data Abstraction platform that automates the extraction and structuring of quality data from electronic health records. Integrated into existing workflows, the system delivers 96% accuracy and can reduce abstraction costs by 50% or more while consolidating registry data in a single location. This enables healthcare organizations to turn quality data into proactive improvement initiatives more efficiently.
Funding
Funding not disclosed
BFFounders
Product
Problem
Healthcare organizations spend a large portion of staff time manually extracting and structuring clinical information from unstructured charts, leading to high abstraction costs, delayed quality reporting, and increased clinician burnout.
Solution
Health Elements AI provides an LLM‑based clinical data abstraction platform that integrates directly into existing workflows. The system ingests medical records in various formats, applies large language models to extract and structure data for registries and quality programs, and delivers results with validated 96% accuracy even on complex queries. By consolidating all registry data in a single, HIPAA‑compliant repository, the platform reduces abstraction costs by 50% or more and frees staff to focus on higher‑value tasks. The solution is delivered via the Carbon Data Abstraction Platform, which offers end‑to‑end data ingestion, AI‑driven extraction, and cloud‑based analytics accessible through a web interface.
Target Audience
Primary customers are hospitals, health systems, and health‑technology vendors that manage clinical registries, quality reporting, and performance improvement programs.
Features
- LLM‑powered extraction engine achieving 96% accuracy on complex clinical questions
- Seamless ingestion of charts in multiple formats with HIPAA‑compliant security
- Unified dashboard that consolidates registry data from disparate sources into one location
- Automated workflow integration requiring minimal changes to existing processes
- Cost reduction of 50%+ by minimizing manual abstraction effort
- Real‑time validation and evidence capture for extracted data fields