Extrico provides an integrated health‑IT platform that converts raw clinical data into actionable information for clinicians, administrators, and researchers. The system streamlines workflows, improves documentation accuracy, and supports revenue management while offering standardized data and scalable patient identification for research. By unifying data across operations, Extrico enables strategic decisions that enhance patient care, operational efficiency, and financial performance.
Funding
Funding not disclosed
Founders
Product
Problem
Healthcare organizations struggle with massive, fragmented electronic health record (EHR) data that is difficult to clean, standardize, and translate into reliable information for clinical, operational, and research use. Inaccurate documentation and missed billing codes further erode hospital revenue and efficiency.
Solution
Extrico provides a unified health‑IT platform that ingests raw EHR data, normalizes it into a structured set of 20 tables, and applies a library of over 500 clinically‑validated phenotypes. The system automatically identifies missing comorbidities, complications, and coding modifiers, delivering precise, evidence‑based insights rather than probabilistic scores. Clinicians receive streamlined workflows and actionable alerts, administrators gain accurate documentation for revenue capture, and researchers obtain standardized datasets for scalable patient identification and analysis. All outputs are delivered through an intuitive interface that supports rapid query, visualization, and export for downstream decision‑making.
Target Audience
Primary users are hospital clinicians, health‑system administrators responsible for revenue cycle and documentation improvement, and academic or industry researchers needing standardized, queryable patient data.
Features
- Automated data cleaning that resolves duplicate identifiers, inconsistent lab and medication codes, and other “dirty data” issues
- Library of 500+ peer‑reviewed clinical phenotypes that translate heterogeneous data into observable patient traits
- Real‑time identification of missed CC/MCC codes to improve billing accuracy and capture up to $50 M in missed revenue opportunities
- Unified view of patient information across 20 standardized tables, eliminating data silos and simplifying cross‑domain analytics
- Role‑based dashboards for clinicians, administrators, and researchers with drill‑down evidence for each insight
- AI‑enhanced analytics that combine clinical expertise with advanced modeling to produce definitive answers