(untitled) (CIPEEX, 2025)
The fragmented landscape of hospital data management systems in Brazil represents a critical barrier to efficient healthcare, resulting in uncoordinated communications and gaps in access to information. In response to these challenges, we propose Mediplanner, a platform still under development, which aims to unify clinical data management and communication between patients and healthcare professionals in a centralized digital environment. Mediplanner will be developed with an artificial intelligence (AI)-driven architecture, enabling the integration and analysis of multiple data sources, such as laboratory tests, medical reports, and consultation histories, with simplified access via mobile devices and desktops. AI will play a key role in optimizing clinical operations, applying predictive algorithms to identify patterns of behaviour and forecast possible absences and cancellations of appointments, making it possible to dynamically adjust specialists’ schedules. In addition, AI will be designed to provide personalized care recommendations, adapted to each patient’s health history, as well as automated reminders for appointments and prescribed treatments. Although the platform is still in the design phase, theoretical studies suggest that the adoption of AI systems such as Mediplanner could result in significant improvements in the operational efficiency of health services, minimizing missed appointments and increasing patient compliance with treatments. The proposal aims not only to optimize operational flows, but also to create a more transparent and personalized care experience for the patient.