AI-Enabled Inclusive Oral-Systemic Integrated Care (AI-IOC+): An Equitable, Learning Framework for Managing Polypharmacy, Multimorbidity, and Special Health Needs Throughout Life

Increased polypharmacy, ineffective resource use, and worse results for people with chronic illnesses, especially older folks and those with specific healthcare needs, are all consequences of the fragmentation of dental and medical services. Few frameworks integrate AI with oral-systemic integration and a life-course, equity-centered approach, despite the fact that AI offers scalable potential to integrate diverse health data, improve clinical decision-making, and promote proactive population health management. Predictive risk modeling for oral-systemic disease clustering, adaptive patient and caregiver interfaces for special populations, AI-assisted clinical decision support, including medication reconciliation and contraindication alerts, and a learning health-system feedback mechanism to optimize care pathways are all included in the proposed AI-Enabled Inclusive Oral-Systemic Integrated Care (AI-IOC+) framework. The AI-IOC+ model, which places a strong emphasis on sustainability, fairness-by-design, data interoperability, and governance, seeks to improve early detection and prevention of systemic complications associated with oral disease, improve access and continuity of care for vulnerable populations, lower adverse drug events through AI-supported deprescribing, and increase healthcare efficiency by reducing duplication. With future prospects including focused scoping reviews, stakeholder co-design pilots, and health economic assessments to enable widespread implementation, this approach offers policymakers, academics, and healthcare systems a useful road map.