AI-Driven Document Intelligence for Integrating EHR and RCM Systems During Hospital System Outages: A Case Study

How can artificial intelligence mitigate unexpected real-world data flow disruptions in digital healthcare systems? Healthcare providers face challenges in documenting care, from initial patient encounters to billing, surveying, and reporting processes. Digital Electronic Health Records (EHR) software systems are used to capture the data from paper documents so they can be transmitted electronically to Revenue Cycle Management (RCM) for billing, claims, and reporting purposes. However, system outages due to crashes, breaches, or other failures can leave healthcare facilities without sufficient human data entry resources to manage the integration of high volumes of paper records between systems. These outages can impact insurance claim approval, provider payments, and timely quality metrics. This case study describes an emergency solution developed to address such an event. We leveraged emergent document intelligence/AI tools and custom software engineering to create a backup system that identified, extracted, and processed data from thousands of scanned paper document used to register patients in the provider RCM system. The solution saved hundreds of hours of manual data entry and helped avoid late insurance claims. It successfully bridged the digital gap between facility and provider until the outage was resolved and served as a permanent backup system that is now being expanded to support more document types from various sources.