Data Driven Recommendation System for Improving Resource Allocation for Hospitals

This study developed a Data-Driven Recommendation System for Improving Resource Allocation for Hospitals, specifically designed for San Antonio District Hospital in San Antonio, Nueva Ecija. It employed a developmental research design using the Agile Development Model to design and implement a secure, web-based system that provides real-time monitoring of hospital equipment, supplies, room and bed availability, and maintenance schedules. The system also generates automated alerts and structured, data-driven recommendations to support administrative and operational decision-making without disrupting existing hospital workflows. System evaluation was conducted using the ISO/IEC 25010 Software Quality Model. Ten (10) IT experts assessed the system across nine quality characteristics, yielding an overall mean rating within the Highly Acceptable range (overall means ranging from 3.70 to 3.80). Thirty (30) hospital staff evaluated the system in terms of functional suitability, performance efficiency, and interaction capability, with results likewise interpreted as Highly Acceptable (overall means ranging from 3.20 to 3.30). These findings indicate that the system meets both technical quality standards and practical operational requirements in a district hospital setting. Overall, the results demonstrate that the developed system effectively addresses limitations associated with manual resource tracking by providing centralized visibility, timely notifications, and data-supported recommendations. The study concludes that the system is suitable for deployment in district hospitals and contributes a practical, scalable approach to data-driven decision support for hospital resource allocation in low-resource healthcare environments.