Two prominent health officials in the United States foresee significant advancements for rural healthcare through the use of artificial intelligence (AI). Robert F. Kennedy Jr., the Secretary of Health, articulated during a Senate panel that AI nurses could offer "concierge care" tailored to those in rural settings. Meanwhile, Mehmet Oz, head of the Centers for Medicare & Medicaid Services, advocated for AI-driven avatars as a promising means of connecting these patients to mental health resources.
Many state health leaders share this vision and are utilizing a portion of the $50 billion federal Rural Health Transformation Program to integrate AI technologies into rural healthcare systems. AI encompasses technologies capable of executing tasks traditionally requiring human intellect, such as identifying patterns or generating text. While AI holds promise for enhancing healthcare efficiency—by streamlining administrative tasks and recognizing at-risk patients—skepticism remains prevalent. Critics argue there is limited evidence demonstrating AI's effectiveness in improving healthcare access and patient health outcomes in rural regions. Additionally, there are concerns regarding how states will monitor and report on the results of their AI investments.
In Hot Springs, South Dakota, home to approximately 3,400 residents, community members expressed caution. Tara Haffner, speaking outside the American Legion, revealed her apprehension about AI's potential errors in personal healthcare, emphasizing the importance of keeping healthcare decisions between patients and their doctors.
Conversely, Phillip Mues, who manages technology at Cherry County Hospital in Valentine, Nebraska, believes AI already enhances clinician efficiency by alleviating administrative burdens, allowing healthcare providers to concentrate more on patient interactions. He remarked, "AI won't replace human workers; rather, it will assist them in rural areas."
Despite these endorsements, Mues acknowledged that AI is not a comprehensive solution, particularly for rural hospitals facing closure or service reductions due to financial constraints.
Established by Congressional Republicans last summer, the Rural Health Transformation Program was created as part of President Donald Trump's broader One Big Beautiful Bill Act. This initiative aims to mitigate the anticipated disruptive effects of a Medicaid spending cut projected to exceed $900 billion over the next decade on rural communities.
Hot Springs, with its 25-bed independent hospital and a VA hospital, is known for its historical architecture and the natural hot springs. However, residents often face long travel times to access advanced medical care. Many individuals interviewed identified cost and long wait times, primarily driven by staffing shortages, as the main issues in their healthcare system.
Doug Nikkila, a heavy equipment operator, pointed out both the advantages and disadvantages of emerging technologies like AI. He suggested that nursing homes could benefit from AI monitoring systems that would help prevent neglect by reminding staff when residents require specific care.
Despite the ongoing adoption of AI in healthcare, a recent ARISE report—supported by experts from Stanford and Harvard—indicates that these innovations are often "poorly evaluated," generating limited real-world evidence of their effectiveness, particularly in rural settings. An academic review highlighted that only 26 peer-reviewed studies on AI's role in rural health were published from 2010 to April 2023, with few examining implementation outcomes.
Some states are daring to explore bold AI initiatives, including AI for diagnostic recommendations. Utah's proposal includes funding for an experimental AI system to manage prescription refill requests, revealing a willingness to experiment despite the risks.
Because AI technologies are typically developed and tested in larger urban hospitals, Qian Huang, a rural health expert at East Tennessee State University, cautioned that outcomes may vary significantly in rural areas, where patients may experience different challenges such as transportation issues.
State plans for the Rural Health Transformation Program are showing interest in employing AI for backend processes like medical coding, prior authorizations, and referrals. States like Washington are exploring how AI can streamline financial recovery processes as well.
Mues shared his clinic's experience with AI scribes that document patient visits, noting a marked decrease in clinician burnout as healthcare providers are able to engage more with their patients without the distraction of computer work.
Several states are also interested in AI’s potential to directly influence patient care. For example, Mississippi aims to use predictive algorithms to aid emergency responders in triaging and routing patients. North Dakota's plan mentions using AI to detect early signs of chronic diseases, while New Hampshire seeks to identify individuals at risk for adverse drug events.
Engaging with patients about AI usage presents additional challenges. For instance, Stephanie Keller from Hot Springs, who uses a fitness-tracking smartwatch, expressed doubts about the practical utility of an AI chatbot encouraging her health efforts. "I don’t have time to chat with AI every day," she remarked.
Rural healthcare facilities encounter unique barriers when adopting AI technologies, such as insufficient infrastructure or IT personnel. Huang noted that staff in these facilities often juggle multiple roles, leaving little time for AI training. Additionally, unstable internet connections may hinder both practices and patients from effectively utilizing AI.
Despite some initial resistance, Mues indicated that many patients at the Valentine clinic have embraced AI applications like scribing. However, the broader acceptance of AI in healthcare remains uncertain.
As AI adoption accelerates, there is an increased risk of rural healthcare organizations entering agreements they might later regret. Jordan Everson, an assistant professor at Georgetown University, noted the urgency for these institutions to carefully evaluate AI tools before implementation.
Some states are attempting to mitigate this risk by creating collaborations aimed at helping rural healthcare facilities select and assess AI applications while providing ongoing support and training.
While the Centers for Medicare & Medicaid Services (CMS) has no specific reporting requirements for AI, they are developing a framework for states to report on their overall progress and outcomes.
Abraham Pritzker from Julota emphasized that states should focus on measuring not just AI usage rates but also tangible health outcomes, such as reductions in falls or emergency room visits.
However, many states' applications to the Rural Health Transformation Program only reference tracking usage metrics without addressing the impact of AI on healthcare delivery. Some may enhance reporting requirements in the future.
States including Connecticut and Texas are planning to monitor outcomes more closely, requiring tracking of patient monitoring devices’ alert accuracy and organizational cost savings, respectively. It's crucial, Huang argues, for states to share findings to prevent wasted resources on ineffective tools.
Through the innovative integration of AI, rural healthcare has the potential to be transformed, provided that both its capabilities and limitations are understood and addressed.
