An AI-driven Low-Code Framework for Healthcare System Digital Transformation
TL;DR
This study proposes a comprehensive framework that leverages low-code RPA to automate complex, rule-based processes, including electronic medical record (EMR) updates, insurance claims processing, and compliance reporting, without requiring extensive software development expertise.
Abstract
The healthcare sector is under increasing pressure to optimize operational efficiency, reduce administrative burdens, and enhance patient-centric services; all while maintaining strict regulatory compliance. This study investigates the integration of Robotic Process Automation (RPA) with low-code development platforms as a transformative approach to healthcare automation. The study proposes a comprehensive framework that leverages low-code RPA to automate complex, rule-based processes, including electronic medical record (EMR) updates, insurance claims processing, and compliance reporting, without requiring extensive software development expertise. Using system architecture modeling, workflow analysis, and proof-of-concept implementation, this research evaluates the technical efficacy, scalability, and security of low-code RPA solutions in healthcare environments. Key contributions include a domain-specific methodology for identifying automation candidates, a modular orchestration model for RPA deployment, and performance metrics demonstrating improvements in task execution time, accuracy, and resource utilization. The study also addresses critical challenges, including interoperability with legacy healthcare information systems, data privacy (e.g., HIPAA compliance), and governance of autonomous processes.