SCHOOL MANAGEMENT SYSTEM: CLINIC (A WEB-BASED SOLUTION FOR CLINIC DATA MANAGEMENT AND MEDICAL RECORDS TRACKING INTEGRATED WITH FORECASTING AI)

Abstract

Bestlink College of the Philippines has consistently prioritized student health and welfare by offering quality healthcare services. However, the school clinic faces several challenges, including time-consuming data entry, error-prone record keeping, and inadequate data security. The lack of a dedicated system also prevents effective tracking of students’ health histories, limiting the ability to implement preventative care strategies to avoid future health complications. To address these issues, a web-based Clinic Management Information System has been developed. This system includes electronic supplies management and integrates advanced forecasting powered by artificial intelligence, which can predict potential underlying illnesses based on symptom patterns and frequent clinic visits. The system is designed to streamline clinic operations while providing data-driven insights for more effective healthcare delivery. The Clinic Management System project adopts the Agile Scrum methodology to support adaptive, iterative development, ensuring timely delivery and responsiveness to user feedback. A Continuous Integration and Continuous Deployment (CI/CD) pipeline was implemented using tools such as Visual Studio Code, Git, GitHub, GitHub Actions, PHP Unit, and Indevfinite. This pipeline automates the entire development lifecycle—from planning and coding to building, testing, deploying, and monitoring. Developers manage both application and infrastructure code through version control, enabling consistent, automated builds and deployments across development, staging, and production environments. The Clinic Management System (CMS) has significantly streamlined clinic operations by reducing manual errors and improving access to accurate and up-to-date medical records. Its AI-powered forecasting capability allows for the early identification of potential health concerns, enabling proactive and preventative care. Overall, the CMS enhances operational efficiency, supports informed decision-making, and strengthens student healthcare services through automation, data analytics, and enhanced data security. The Clinic Management System features secure record management, AI-based health forecasting, one-time password (OTP) authentication, data visualization, and role-based access control (RBAC). Planned future upgrades aim to improve the accuracy of AI forecasts through machine learning, expand communication via SMS notifications and two-way messaging, and transition to cloud infrastructure for greater scalability. Additional enhancements will focus on strengthening security measures and incorporating user feedback to support continuous system improvement and adaptability.