PRINTMED: Utilization of Facial Verification in the Records Management System for Outpatient Services of Carmona Hospital and Medical Center

This study developed PrintMed, a Facial Verification-Based Patient Records Management System (PRMS), to enhance the efficiency, security, and quality of outpatient services at Carmona Hospital and Medical Center. Traditional paper-based records presented persistent challenges, including delayed data retrieval, record duplication, and unauthorized access risks. PrintMed addresses these issues through biometric facial recognition using Amazon Rekognition, enabling secure, contactless, and real-time patient identification. Anchored on the Health Information Systems (HIS) Theory, the Technology Acceptance Model (TAM), and Systems Theory, the study employed a mixed-methods approach, integrating quantitative performance metrics with qualitative user feedback. Developed via Agile-Scrum methodology, the system emphasized iterative design and user-centered testing. Key findings demonstrated substantial improvements in patient check-in times, accuracy of identity verification, prevention of duplicate records, and auditability through comprehensive logging mechanisms. Evaluation using ISO/IEC 25010:2011 standards showed high performance, with mean scores in security (4.60), functional suitability (4.45), usability (4.44), and reliability (4.44), reflecting strong acceptance among hospital staff and patients. These results confirm that biometric-enhanced PRMS can significantly improve outpatient healthcare data management and service delivery, particularly in high-volume clinical settings. To further maximize impact, the study recommends expanding PrintMed to other hospital units, integrating billing and inventory systems, developing a patient-facing mobile application for appointment scheduling and teleconsultation, incorporating multilingual support, and implementing analytics dashboards for administrators. Such enhancements would foster holistic workflow integration, improve patient engagement, ensure inclusivity, and enable data-driven decision-making, offering a scalable, privacy-compliant model for digital health transformation and informing future policies and system implementations in Philippine healthcare settings.