Ensemble Health Partners Optimizes Healthcare Revenue Cycle with Generative AI
Ensemble Health Partners, a leading U. S. provider of revenue cycle outsourcing for healthcare, partnered with Microsoft to infuse generative AI and machine learning into its EIQ revenue cycle intelligence platform. EIQ processes data from hundreds of disparate systems, aggregating more than 800 terabytes of data, and integrates insights directly into healthcare providers' EHRs. By leveraging Microsoft Azure, Azure Machine Learning, Azure AI, and Azure Generative AI, Ensemble automates workflows, improves denial resolution, and optimizes revenue collection management at scale. The partnership supports rapid deployment of hundreds of AI models, enabling real-time automation and workflow guidance for revenue cycle operators. In 2023, Ensemble prevented over $200 million in lost revenue for healthcare clients, generated tailored appeal letters with AI, and improved overall financial outcomes across its national client base. Notably, the innovations contributed to Ensemble winning multiple industry performance awards and expanded strategic partnerships with major U. S. health systems. Ensemble's investment in AI and process automation (2 million development hours and $100 million over a decade) resulted in a robust platform that also supports continuous model improvements and data harmonization, ensuring best-in-class outcomes for healthcare organizations.
- Organization
- Ensemble Health Partners
- Industry
- Healthcare
- Location
- United States
- Published
- April 2024
Reported outcomes
+5%
revenueRevenue & growth
Strategic outcomes
Catalog median for revenue & growth deployments: +34% across 150 reported metrics. Compare benchmarks →
Primary read
Use case focus
Showing 3 of 3
- 1Automated Revenue Cycle Management in Healthcare
- 2Generative AI for Denial Resolution and Appeals
- 3AI-Powered Decision Support in Billing and Collections
- Healthcare organizations face complex and costly revenue cycle processes.
- Lost revenue due to inefficient claims and denial resolution processes.
- Administrative cost pressures in managing large-scale healthcare billing and cash collection.
- Difficulty harmonizing data across hundreds of disparate systems.
- Need for real-time automation and actionable insights in revenue cycle operations.
- Implemented EIQ intelligence engine powered by Microsoft Azure, Azure AI, Azure Machine Learning, and Generative AI.
- Aggregated and harmonized over 800 terabytes of healthcare data.
- Integrated AI-driven workflows, denial resolution, and cash collection optimizations into healthcare providers' EHRs.
- Deployed hundreds of generative AI models to automate decisions and guide operator actions.
- Continuous model improvement via collaboration of engineers, operators, and data scientists.
- Prevented over $200 million in lost revenue for clients in 2023.
- Accelerated denial resolution with AI-generated appeal letters.
- Improved cash collections and revenue yield; on average, 5% net revenue improvement per year for clients.
- Managed $32 billion in annual net patient revenue across hundreds of healthcare organizations.
- Multiple awards for best revenue cycle outsourcing and outstanding client performance results.
Architecture
EIQ aggregates and harmonizes data from hundreds of disparate systems (>800TB), integrates insights and AI-driven automation directly into healthcare organization EHRs, leverages Microsoft Azure (incl. Azure Machine Learning, Azure AI, Azure Generative AI), and supports rapid deployment of generative AI models that process millions of healthcare transactions daily. Models are continuously improved and embedded in operational workflows, guiding operator actions and ensuring optimal revenue cycle outcomes.
Sources & evidence1
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