U.S. Healthcare Provider Recovers $2.1M Annually with GenAI-Powered Clinical Documentation Optimization

Case Study

U.S. Healthcare Provider Recovers $2.1M Annually with GenAI-Powered Clinical Documentation Optimization

At A Glance

Overview

Our client was experiencing significant financial and operational strain due to chronic undercoding caused by ambiguous physician documentation. Manual coding processes led to frequent inaccuracies, contributing to ongoing CMS audits and an estimated revenue loss of $42,300 each month. These challenges extended the revenue cycle, increased administrative burden, and heightened regulatory risk. Like many U.S. healthcare providers, our client was not alone; manual coding errors contribute to nearly $564 million in annual losses nationwide, with 63.4% of billing issues stemming from human error.

Our Solution

We implemented a GenAI-powered clinical documentation optimization platform that leverages Natural Language Processing (NLP) and Retrieval-Augmented Generation (RAG) to streamline medical coding and improve documentation accuracy:

  • Accelerated Workforce Enablement: AI-generated coding rationales reduced training time and improved ramp-up consistency, accelerating coder onboarding by 80%.
  • Optimized Operational Throughput: Automated extraction of diagnosis and procedure codes minimized manual workload and significantly boosted coder productivity.
  • Strengthened Compliance and Oversight: Built-in audit trails and explainable code justifications enhanced transparency, reduced audit risk, and supported regulatory compliance.
  • Seamless Integration and Scalability: Full compatibility with existing EHR systems via aiH.Automate ensured smooth deployment across clinical departments and scalable adoption network-wide.

Impact and Results

The implementation delivered clear, quantifiable business results that significantly outpaced industry standards. The organization saw a substantial drop in coding-related claim denials, far outperforming typical benchmarks. Revenue recovery improved notably as better code capture accuracy translated directly into millions in reclaimed income. Additionally, coder onboarding became dramatically faster, thanks to the support of explainable GenAI tools. Together, these outcomes strengthened operational resilience and accelerated performance across the revenue cycle. 

This GenAI-powered transformation positioned our client to reduce financial leakage, elevate compliance standards, and scale documentation quality across their healthcare network.

Key Technologies

  • Cloud Platform: Microsoft Azure (Azure Machine Learning, Azure App Service, Azure Kubernetes Service, Azure Data Factory, Azure Event Hubs).
  • AI & NLP: OpenAI GPT models, Azure Cognitive Services – Text Analytics, Named Entity Recognition (NER), Retrieval-Augmented Generation (RAG).
  • Integration & Interoperability: FHIR APIs, HL7 Interfaces, aiH.Automate, Azure Logic Apps.
  • Development Frameworks: Python, .NET Core, React.
  • Data Security: HIPAA-compliant architecture, Azure Key Vault, Role-Based Access Control (RBAC), Secure API Gateway, Audit Logging.
  • 58%
    Reduction in coding-related claim denials, compared to a 22% industry average.
  • $2.1 Million
    Annual revenue recovery through improved code capture accuracy.
  • 72%
    Faster coder onboarding, driven by explainable GenAI support tools.
Download PDF