Andrew M. Ibrahim MD, MSc, FACS
General Surgeon at University of Michigan, Chief Clinical Officer at Viz.ai
Rural communities face persistent gaps in healthcare access, quality, and outcomes that leave patients underserved and health indicators worse than in urban areas. Now, AI can directly address these rural care barriers.
California is home to more than 39.5 million residents, including more than 2.7 million people living in rural communities across 57 counties. To strengthen care delivery in these geographically dispersed areas, the California Rural Health Transformation program plans to build hub-and-spoke regional networks that expand access and improve coordination across the continuum of care.
This is a complex challenge. Rural communities and tribal populations often face long travel times to reach primary, maternity, and specialty care, with some residents traveling hours for appointments. Workforce shortages and higher rates of chronic disease further strain local health systems.
Preventable mortality rates for conditions such as heart disease and stroke remain higher in rural counties, underscoring the need for earlier detection and faster intervention. AI-enabled technologies can help connect local providers with regional specialists, support real-time clinical decision-making, and ensure patients receive the right care close to home whenever possible.
Viz.ai’s platform provides AI-powered disease detection and intelligent care coordination, helping rural providers manage complex and time-sensitive conditions more effectively, without adding workflow burden.
Specialists can review 3D imaging alongside an AI-generated patient summary built from ambient listening and EHR data, and make referrals directly within Viz.ai’s HIPAA-compliant mobile app. This accelerates diagnosis and streamlines coordination across care teams.
Viz.ai helps rural California health systems:
Together, these capabilities help deliver faster care, better access, and more sustainable rural healthcare across California.
1
Early detection and triage at the point of care
AI can rapidly analyze imaging and clinical data to flag suspected disease and critical findings in minutes, even in hospitals without on-site specialty coverage. This accelerates diagnosis and enables faster treatment or transfer decisions.
2
Decision support for rural care teams
Rural emergency departments are often staffed by generalists managing high-acuity cases. AI tools support guideline-based decision-making by surfacing and sharing actionable insights in real time, mitigating workforce shortages without replacing clinical judgment.
3
Care coordination across fragmented systems
Critical and acute care frequently require coordination across EMS, emergency departments, imaging, specialists, and receiving centers. AI platforms like Viz.ai unify these workflows, ensuring the right teams are alerted and aligned quickly—critical in rural settings.
AI software for stroke is recognized in American Heart Association (AHA) guidelines as a tool to support early detection, triage, and clinical decision-making in acute stroke care.
This matters for rural health policy. The inclusion of AI in AHA guidelines signals that these technologies are clinically validated, evidence-based, and appropriate for broad adoption, not pilot-only experimentation.
In rural settings, platforms like Viz.ai can enable faster identification of suspected disease, support earlier activation of care and transfer pathways, reduce time to treatment, and improve consistency of care across low-volume and resource-constrained hospitals.
Hear from Dr. Andrew Ibrahim, Chief Clinical Officer at Viz.ai, in a congressional hearing on AI in healthcare, on how AI-powered care coordination specifically helps rural communities and patients.