Abstract
iTrackMed: A Smart Inventory System with Predictive Analytics for the Central Supply Unit (CSU) of Ospital ng Lungsod Agham ng Muñoz (OSLAM) was developed and evaluated in this study. The existing inventory process relied on Microsoft Excel and paper-based records, leading to data inaccuracies, delayed updates, limited real-time visibility, and the absence of demand forecasting. A system development and evaluation methodology using Agile Software Development Life Cycle was employed. The system automated inventory tracking, approvals, item issuance, and reporting, and integrated time-series forecasting and predictive analytics to analyze historical consumption data and forecast future demand. System evaluation utilized the ISO/IEC 25010 software quality model and the Technology Acceptance Model (TAM). Results indicated high levels of functionality, usability, reliability, and security, with users perceiving the system as useful and easy to use. The incorporation of predictive analytics significantly improved inventory planning and decision-making. Overall, iTrackMed was found to be an effective solution for improving inventory management in a public hospital setting.
Keywords: Smart Inventory System, Predictive Analytics, Hospital Inventory Management, ISO/IEC 25010, Technology Acceptance Model
https://doi.org/10.65494/pinagpalapublishing.65
