AI-Powered Telehealth

Rural healthcare organizations use telehealth to expand access to healthcare services among patients who face barriers such as long travel distances, transportation challenges, provider shortages, and stigma around conditions like mental health or substance use disorders. Telehealth can also help healthcare providers to reach patients in their homes and connect them to services that may otherwise be unavailable where they live, such as specialty care, mental health services, and pharmacy services. The Rural Telehealth Toolkit describes evidence-based telehealth program models in rural communities.

Combining AI and telehealth is described as a "transformative opportunity to enhance healthcare delivery, particularly in rural settings." AI can increase the effectiveness of telehealth in rural healthcare settings by supporting remote diagnosis, treatment, and follow-up care.

There are many different AI-powered telehealth applications in rural healthcare organizations, including:

• Predictive analytics for early detection and intervention (see AI-Enabled Predictive Analytics Model)
• Image analysis of X-rays, CT scans, and MRIs, to detect disease (see the AI-Powered Image Analysis Model)
• Patient remote monitoring, for example, using wearable health technologies (see Remote Patient Monitoring Model)
• Chatbots and digital assistants (see Conversational Agents)
• Triage bots to assess symptoms and direct patients to appropriate care levels

AI has been applied to telehealth in many medical specialties, with the strongest evidence for AI-enabled telehealth in the areas of teledermatology, ophthalmology, maternal health, and oncology. AI has also been incorporated into telehealth for mental health and chronic disease management, although the evidence in these areas is still developing. Additional applications include using AI to support robotic-assisted examinations and robotic telesurgery.

Examples of Rural Programs Using AI-Powered Telehealth

• Sanford Health in South Dakota is leveraging telemedicine and AI to overcome geographic barriers and expand access to high-quality healthcare in rural areas. Sanford clinicians are delivering general and specialty care remotely. AI and telehealth are central to its strategy for improving health outcomes, increasing provider efficiency, and ensuring that rural patients can access timely care.
• The University of Michigan is leading a project with federal funding from the Advanced Research Projects Agency for Health to develop AI-powered mobile clinics. The clinic is physically mobile and will combine in-person care and AI-enabled telehealth support. The project is designed to improve healthcare access, reduce costs, and help address workforce shortages in rural areas.

Considerations for Implementation

The evidence on AI-driven telehealth is emerging, with additional research and evaluation needed on the application of AI in telehealth, particularly in rural settings. Challenges to AI-powered telehealth include limited broadband internet access, varying levels of digital literacy, and concerns about privacy and data security.

Healthcare providers, including clinicians, nurses, and other staff, need education and training to use AI-powered telehealth tools effectively (see Training and Capacity Building). In addition, AI models and tools must be effectively integrated into existing infrastructure and operations. Interoperability challenges can limit integration across telemedicine platforms and electronic health record systems. Bias in AI models also affects implementation of AI-powered telehealth. This is a broader challenge affecting AI in rural healthcare, in general, given the underrepresentation of rural populations in many datasets.

Resources to Learn More

AI in Telehealth
Video/Multimedia
Discusses AI use in healthcare and telehealth.
Organization(s): Southwest Telehealth Resource Center
Date: 1/2024

Integrating Artificial Intelligence into Telemedicine: Evidence, Challenges, and Future Directions
Document
Reviews the evidence on the application of AI in telemedicine and explains how AI-enabled tools can enhance remote healthcare delivery.
Author(s): Rossi, M. & Rehman, S.
Citation: Cureus, 17(8), e90829
Date: 8/2025

Investigation into Application of AI and Telemedicine in Rural Communities: A Systematic Literature Review
Document
Synthesizes evidence on how AI and telemedicine are used to improve healthcare delivery in rural communities and summarizes challenges such as digital literacy, access, and ethical considerations.
Author(s): Perez, K., Wisniewski, D., Ari, A., et al.
Citation: Healthcare, 13(3), 324
Date: 2/2025