Integrating AI and Telehealth: A Series for Academic Medical Centers

Manatt Health and the Telehealth Centers of Excellence at the Medical University of South Carolina (MUSC) and the University of Mississippi Medical Center (UMMC) collaborated on a series of white papers to identify and describe opportunities to integrate artificial intelligence (AI) within telehealth to support broader scaling and adoption. The series of four briefs feature different telehealth use cases, outlining barriers to adoption, opportunities to integrate AI across care delivery workflows, and considerations for research and policy. Briefs are based on background research and expert interviews with health system and telehealth vendor leaders.

Integrating AI and Telehealth: eConsults

eConsults have been critical for expanding timely access to specialty care, particularly in regions with limited access to specialist workforce, by enabling asynchronous, provider-to-provider consultation without requiring immediate face-to-face specialist visits. eConsults have been shown to reduce unnecessary specialty referrals, especially for lower-complexity clinical questions, reserving in-person specialty time for patients who need it most.While adoption of eConsults has increased since coverage and payment became permissible under Medicare in 2019 and under Medicaid and the Children’s Health Insurance Program (CHIP) in 2023, scalability remains constrained by a combination of workflow burden and billing constraints.

AI offers practical opportunities to support greater provider uptake of eConsults and expand access to specialty expertise by streamlining workflows and reducing administrative burden. With coordinated strategy, policy, and research, AI can help scale eConsult programs and advance more timely, efficient access to specialty care.

Read the full report .

Integrating AI and Telehealth: Remote Patient Monitoring

Rural and medically underserved areas face higher rates of chronic disease and related mortality, exacerbated by workforce shortages that limit access to specialty care and can lead to fragmented longitudinal care.Remote patient monitoring, including remote physiological monitoring (RPM) and remote therapeutic monitoring (RTM), has emerged as a care model that can address access concerns by extending clinical oversight between visits through biometric monitoring and tracking of patient-reported outcomes, and supporting provider clinical decision-making beyond what is feasible through direct in-person or virtual encounters alone.Although utilization of RPM and RTM has grown, challenges to widescale adoption remain, including limited patient engagement, variability in coverage across payers and states that creates financial uncertainty for providers, and operational complexity that may limit program scalability.

As AI technology matures, its integration into RPM and RTM programs may support broader adoption by addressing workflow challenges, improving clinical impact, and strengthening financial return on investment of monitoring services. AI can streamline burdensome administrative processes for care teams and support providers in targeting RPM and RTM resources toward the patients and conditions where monitoring has demonstrated the most clinical benefit, helping build the evidence base for effective use and reinforcing the case for broader payer adoption.

Read the full report .

Integrating Artificial Intelligence (AI) into Virtual Nursing Programs

Health systems are turning to virtual nursing to address staffing challenges, reduce workload for in-person nursing teams, and improve patient safety. By shifting tasks that can often be safely completed remotely to virtual nurses (e.g., admissions, discharge, and documentation) bedside staff can focus on hands-on patient care. This more efficient allocation of nursing resources drives measurable improvements in patient monitoring, staffing costs, and nurse and patient satisfaction.

While still in the early stages of implementation, AI has potential to support virtual nursing adoption and scaling by improving provider and patient experience across the virtual nursing workflow.

Read the full report .

Integrating AI and Telehealth: Asynchronous Electronic Visits (eVisits)

Health systems face growing patient demand alongside a limited supply of health care providers, straining their capacity to deliver timely primary and specialty care. eVisits can improve patient access by enabling patients to submit clinical concerns 24/7, which providers can then review and respond to asynchronously. This approach reduces reliance on scheduled synchronous telehealth or in-person visits, giving patients greater flexibility and enabling more efficient care delivery.

Integrating artificial intelligence (AI) into eVisits can strengthen their potential to increase access to care by addressing operational and structural barriers to adoption, such as patient accessibility and safety concerns, and provider administrative burden. 

Read the full report .

Bhargava R, Gayre G, Huang J, Sievers E, Reed M. Patient e-Visit Use and Outcomes for Common Symptoms in an Integrated Health Care Delivery System. JAMA Netw Open. 2021;4(3):e212174. doi:10.1001/jamanetworkopen.2021.2174