Andrew M. Ibrahim MD, MSc, FACS
General Surgeon at University of Michigan, Chief Clinical Officer at Viz.ai
Closing Rural Care Gaps with Clinically Proven 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.
AI-Enabled Access to Critical Specialist Care for Rural Montana
Montana Department of Public Health & Human Services plans to deploy AI-enabled technology to improve access to time-sensitive emergency medicine and stroke care for rural and tribal communities across the state.
This is a complex challenge. Nearly half of Montana’s residents live in one of the state’s 51 rural counties, with an additional 12% living in rural tracts within its five urban counties. These communities are widely dispersed, with an average of just 4.1 people per square mile in rural areas.
Access to specialty care is limited. Montana’s rural counties average only 77 physicians per 100,000 people, and patients in 15 counties must travel more than 20 miles to reach a hospital. In four counties, that distance exceeds 40 miles, delaying care when minutes matter most.
How Viz.ai Supports Rural Montana
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 Montana health systems:
- Shorten time to diagnosis and treatment
- Improve patient longevity and quality of life
- Reduce unnecessary transfers to distant referral centers
- Support EMS, emergency departments, and specialty teams within existing workflows
- Scale rapidly across regions and statewide networks
Together, these capabilities help deliver faster care, better access, and more sustainable rural healthcare across Montana.
AI-powered care solutions address rural challenges in three ways that traditional models cannot
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-Powered Care Included in the AHA Guidelines
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.
