2nd Edition of Preventive Medicine World Conference 2026

Abstract

The sustainability of healthcare systems has emerged as one of the greatest challenges of the 21st century. Population aging, the growing prevalence of chronic diseases, and the continuous rise in healthcare expenditures require innovative approaches capable of simultaneously improving clinical outcomes, operational efficiency, and financial sustainability. Although preventive medicine is widely recognized as a critical strategy for addressing these challenges, most current models remain predominantly centered on primary care and often struggle to identify high-risk individuals early enough to prevent disease progression. In response to this limitation, Unimed Caruaru developed and implemented an innovative population health management model supported by the artificial intelligence platform Previne.AI. Unlike traditional preventive care programs, the model utilizes data generated throughout the entire healthcare journey of beneficiaries, including outpatient consultations, specialist visits, laboratory tests, diagnostic imaging, hospital admissions, and administrative records.

Artificial intelligence algorithms continuously analyze these data sources to identify risk patterns, stratify populations, automate preventive interventions, and support evidence-based clinical decision-making. A retrospective observational analysis was conducted between 2024 and 2026 to evaluate the clinical, epidemiological, and economic impacts of the implementation. Significant improvements were observed across multiple care programs. In colorectal cancer screening, the proportion of colorectal cancer cases within the oncology portfolio decreased from approximately 9.2% to 1.6%, while early detection initiatives identified high-risk lesions requiring immediate intervention. The program generated an estimated cost avoidance exceeding BRL 1.3 million from an investment of only BRL 35,000. Breast cancer screening programs demonstrated increased coverage and earlier-stage diagnoses, reducing advanced-stage presentations by approximately 7% and generating estimated avoidable costs exceeding BRL 600,000.

Chronic disease management programs achieved high patient engagement, with 82% participation in intensive care pathways and 80% of participants achieving more than 70% of established clinical targets. Additional benefits were observed among chronic kidney disease patients, including reductions in healthcare expenditures and increased transplantation rates. Corporate health programs also demonstrated substantial reductions in claims ratios and improved financial performance. The experience suggests that integrating artificial intelligence, predictive medicine, and population health management creates a new paradigm for preventive healthcare. By transforming data generated across secondary and tertiary care into active preventive intelligence, Unimed Caruaru has developed a scalable and potentially replicable model capable of improving health outcomes while enhancing the sustainability of healthcare systems worldwide.