A Framework for Intelligent Hospital Automation and Decision Support Using RPA and Business Intelligence

Hospitals today operate in highly complex environments where administrative efficiency and timely decision-making are as critical as clinical excellence. Manual and semi-automated hospital workflows often lead to scheduling conflicts, uneven resource utilization, and limited operational visibility. In this context, intelligent automation and analytics have emerged as key enablers of digital transformation in healthcare administration. This paper presents a conceptual framework for intelligent hospital automation and decision support that integrates Robotic Process Automation (RPA) with Business Intelligence (BI) techniques. The proposed framework focuses on automating core administrative workflows such as patient appointments, doctor workload management, and pharmacy operations, while simultaneously transforming operational data into analytical insights for hospital management. By combining automation-driven data generation with analytics-based decision support, the framework aims to enhance operational transparency, improve resource utilization, and support informed administrative decisions. The study adopts a system-oriented and analytical perspective, positioning the framework as a scalable and adaptable model for modern hospital information systems.