R1RCM improves healthcare revenue cycle management with AI coding automation
R1RCM, a leading provider of technology-driven solutions for healthcare providers across the US, expanded its collaboration with Microsoft to accelerate the integration of generative AI into its revenue cycle management platform. Using Microsoft Azure OpenAI Service and Azure AI Studio, R1RCM developed and deployed a large language model (LLM)-powered application for physician coding quality assurance. This application evaluates unstructured medical records to predict evaluation and management codes, greatly improving coding quality across patient charts. The LLM application was delivered in under four months and is already increasing productivity for healthcare revenue cycle teams. Looking forward, R1RCM plans to expand the use of generative AI to automate processes such as call centers, payer follow-up, scheduling, and accounts receivable. With a customer base comprising 95 of the largest 100 health systems in the US, R1RCM leverages insights from over 500 million medical records, supporting $900 billion in total net patient revenue. The project aims to drive cost reductions, enhance financial performance, and deliver a better experience for both healthcare providers and patients.
- Organization
- R1RCM
- Industry
- Healthcare
- Location
- United States
- Published
- November 2023
Reported outcomes
Strategic outcomes
Primary read
Use case focus
Showing 3 of 3
- 1Automated Physician Coding Quality Assurance for Medical Records
- 2AI-powered Medical Chart Evaluation and E/M Code Prediction
- 3Revenue Cycle Process Automation Using LLMs
- Healthcare providers face significant financial and staffing challenges.
- Existing revenue cycle management processes are labor-intensive and costly.
- Health systems require improved accuracy in physician coding and quality assurance for medical records.
- There is a need for scalable technology-driven solutions to improve financial outcomes and efficiency.
- Deployed a proprietary large language model (LLM) application using Microsoft Azure OpenAI Service and Azure AI Studio.
- Integrated the LLM into R1RCM's revenue cycle management platform to automate evaluation and management code predictions from unstructured medical records.
- Developed the application in less than four months and rolled out productivity-boosting features for coding quality assurance.
- Planned further AI integration for automating call centers, payer follow-up, scheduling, and accounts receivable.
- Improved productivity for medical coding quality assurance teams.
- Reduced operational costs by automating manual tasks.
- Leveraged insights from 500 million analyzed records and $900 billion net patient revenue.
- Supported 95 of the top 100 US health systems.
- Enhanced patient and provider experience and accelerated time to value.
Architecture
R1RCM integrated Microsoft Azure OpenAI Service and Azure AI Studio into its proprietary revenue cycle management platform, enabling a large language model-based application to analyze unstructured medical records, predict evaluation and management codes, and automate quality assurance. The roadmap includes expanding generative AI automation to other revenue cycle functions such as call centers, scheduling, and accounts receivable.
Sources & evidence1
The same organization appears in newer AI deployment evidence.
- Same organization re-documented as recently as 2024.
Measures whether this deployment's public evidence persists — not whether the system is still in production.
AI-generated summary. Verify important details with the linked sources before relying on this case.
Explore related AI use cases
Was this useful?