AVI AI-enabled Continuity-of-Care Data Infrastructure System: A Modular Health Data Architecture for Longitudinal Tracking Across Maternal, Tuberculosis, and Cervical Cancer Care Pathways in Nigerian Teaching Hospitals

The AVI AI-enabled Continuity-of-Care Data Infrastructure System is a foundational digital public health infrastructure designed to address one of the most persistent challenges in fragmented health systems: the inability to track patients longitudinally across multiple service delivery pathways. In many low- and middle-income country (LMIC) health systems, maternal health, tuberculosis (TB), and cervical cancer services operate as siloed programs with limited interoperability, resulting in fragmented records, poor continuity of care, and high rates of loss to follow-up. This limits the ability of health systems to evaluate service effectiveness, optimize care delivery, and implement data-driven interventions. This system introduces a modular, interoperable, and AI-ready health data architecture designed specifically for deployment in resource-constrained teaching hospital environments. It integrates facility-level electronic medical records, laboratory systems, and programmatic disease registries into a unified longitudinal patient tracking framework using privacy-preserving patient linkage methods. Rather than functioning as a standalone software tool, this system is positioned as a foundational digital public health infrastructure layer enabling longitudinal care evaluation and AI-driven health system optimization in fragmented LMIC service delivery contexts. The architecture is designed to support implementation research, routine health system monitoring, and advanced analytics including continuity-of-care measurement, dropout detection, and service utilization modelling across maternal health, TB, and cervical cancer care pathways.