Intelligent EOB/ERA Generation and Validation Framework on Legacy Systems like Mainframes

Abstract

The​‍​‌‍​‍‌ automated system for generating Explanation of Benefits (EOB) and Electronic Remittance Advice (ERA) is a major development in healthcare revenue cycle management (HRCM) that first of all, addresses the problem of the organizations that are still using traditional mainframe systems. The conventional EOB/ERA processing is loaded with inefficiencies, data inconsistencies, and compliance risks due to the fact that these processes are done manually and the housed architectures are rigid. This research presents a smart model that uses AI, RPA, and middleware technologies to interact with the systems in order to enable the data to be extracted, transformed, and validated without any barriers. The model uses AI-powered data mapping and validation techniques to ensure the execution of HIPAA and other payer’s standards, and at the same time, RPA is responsible for the automation of the repetitive activities like the reconciliation of claims and the documents. The middleware modules are the intermediate layers between the modern APIs and the COBOL-based systems that are allowing communication without compromising the connectivity of the systems. In the case study, the results are so astonishing that they imply a radical shift in the healthcare organization's methods, where they shorten their output time by more than sixty percent, practically eliminate errors through an automated validation process, and significantly increase compliance accuracy through AI-based auditing. It proposes a far-reaching and evolutionary step of a healthcare payment system towards intelligent, compliant, and interoperable ecosystems, providing a scalable and adaptable solution for healthcare organizations to modernize financial communications while saving their IT ‍​‌‍​‍‌investments.