Uses machine learning algorithms to predict high-cost medical claims at the member level, enabling more accurate underwriting for self-funded employers, stop-loss carriers, and risk-bearing entities. By identifying potential catastrophic events from chronic, complex, and rare diagnoses, it helps reduce financial risk and improve cost management in health plans.
Funding
$2M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
LVFounders
Product
Problem
Underwriting and risk management in self-funded healthcare plans are hampered by the difficulty in predicting high-cost medical claims at the individual member level. Inaccurate risk assessment leads to financial instability for stop-loss carriers, employers, and other risk-bearing entities due to unforeseen catastrophic healthcare events.
Solution
Merit Medicine offers an AI-powered predictive analytics platform that forecasts high-cost healthcare claimants, enabling more accurate and data-driven underwriting. By leveraging machine learning algorithms and analyzing billions of data points, the platform identifies potential high-cost events stemming from chronic, complex, and rare diagnoses 12-18 months in advance. This allows for proactive care navigation, early intervention, and optimized stop-loss deductible specifications. The platform provides insights into historical, current, and predicted healthcare spending, empowering stakeholders to manage risk proactively and improve financial outcomes.
Target Audience
Merit Medicine serves stop-loss carriers, managing general underwriters (MGUs), benefits consultants, and plan sponsors seeking to improve underwriting accuracy and manage healthcare risk more effectively.
Features
- AI-powered machine learning model for predicting individual member healthcare costs.
- Identification of future catastrophic claimants 12-18 months in advance.
- Prediction of total first-dollar claims by group, across the book of business.
- Optimization of stop-loss spec deductible for each group.
- Identification of gaps in care for proactive health plan management.
- Analysis of historical spend, total current spend, and total predicted spend distribution.
- Data-driven recommendations to improve financial outcomes and health plan performance.