Introduction

Imagine a family physician working in a rural southeastern county. She comes to the clinic each day with a full schedule, typically 28 patients, knowing that her next available appointment is not for at least three months. Specialty care requires hours of driving and often involves an even longer wait. Her patients deeply appreciate and depend on her for almost all their health needs, typically bringing 5 to 7 concerns to each visit.

Our doctor brings rigorous training and a passion for improving rural health to her practice. At the same time, she struggles with the daily burden of typing notes for 28 visits and keeping up with the incredibly broad and deep knowledge base needed to care for her patients’ many medical conditions. People in her community live with more frequent chronic conditions that are typically managed in primary care because specialty consultation is relatively inaccessible.

At this point in time, rural North Carolina stands to benefit tremendously from adoption of artificial intelligence (AI) tools, although practices often get by with only basic technologies. The Rural Health Transformation Program (RHTP) provides a narrow but vital window to provide this upgrade.

North Carolina and the Southern Rural Health Landscape Face Many Challenges

It is important to recognize some of the many issues that drive adverse health outcomes in North Carolina’s vast rural spaces.

Primary Care Workforce

Impact on adults. One-third of rural residents live in federal health professional shortage areas (HPSAs); 82% of rural counties are medically underserved; primary care physician supply declined in southern and rural counties from 2010 to 2019.1–3

Impact on children. Limited pediatrician availability contributes to gaps in vaccination and preventive care across North Carolina’s 100 counties.

North Carolina context. In the US South, primary care physician supply per capita has declined over the past decade; rural hospital closures are associated with an average 8.2% annual decrease in primary care physician supply in the 6 or more years after closure.3

Rural Hospital Closures

Impact on adults. Counties with 2 hospital closures had a 4.9% reduction in receipt of preventive services among older women and a 3.8% decrease among older men. Mean travel to the nearest hospital is approximately 16 miles/23 minutes in the rural South. Hospital closures are also associated with longer emergency medical service transport and total activation times, increasing risk for time-sensitive cardiovascular and trauma care.3–5

Impact on children. Closure of local hospitals can eliminate pediatric and emergency services, leaving families with longer transport times for acute illness.

North Carolina context. Since 2010, North Carolina has experienced 8 rural hospital closures or conversions into non-acute facilities.

Higher Smoking Rates and Culture of Tobacco

Impact on adults. North Carolina lies within “Tobacco Nation,” where approximately 22% of adults smoke compared with 15% nationally; rural smoking prevalence reaches 28.5%. Smoking accounts for approximately 30% of all cancer deaths.6–9

Impact on children. Approximately 35% of rural children live in a household where someone smokes. Rural adolescents begin smoking earlier and experience greater secondhand smoke exposure at home and school.9,10

North Carolina context. North Carolina’s tobacco-growing heritage contributes to fewer smoke-free laws and weaker tobacco-control policies compared with the rest of the United States. Rural persistent-poverty counties have the highest smoking prevalence and lung cancer incidence and mortality.6–9

Lower Vaccination Rates

Impact on adults. Rural adults have higher hospitalization rates for vaccine-preventable conditions, with rural communities in the Southeast showing consistently elevated rates across demographic groups.11

Impact on children. Childhood 7-vaccine series coverage is 62.6% in small town/rural areas versus 71.2% in urban areas. North Carolina HPV vaccination averages approximately 29% among 11- to 12-year-olds statewide, with substantial county-level variation.12–14

North Carolina context. North Carolina-specific analyses indicate that social vulnerability and pediatrician density, rather than rurality alone, are important predictors of county-level vaccination disparities, suggesting systemic access barriers.14

Chronic Disease Burden and Health Disparities

Impact on adults. Rural southern counties have higher rates of heart disease, stroke, diabetes, chronic obstructive pulmonary disease (COPD), and all-cause mortality. Lung cancer incidence and mortality are highest in rural persistent-poverty counties.8,9,15

Impact on children. Rural children face higher obesity rates, greater agricultural chemical exposures, and limited access to subspecialty management of chronic conditions.

North Carolina context. North Carolina’s eastern rural counties overlap with persistent poverty and the Diabetes Belt, creating compounding risk for cardiovascular disease, cancer, and metabolic disease.15

Geographic and Transportation Barriers

Impact on adults. Mean travel to the second-nearest hospital is 26.4 miles/35 minutes in the rural South. Limited broadband can restrict telehealth as a mitigation strategy.4,5,16

Impact on children. Longer emergency medical service transport times following hospital closure can substantially increase travel time, while geographic barriers reduce access to routine well-child care.16

North Carolina context. North Carolina’s rural geography—from the Appalachian west to the Coastal Plain east—creates distinct access challenges requiring regionally tailored solutions.

Technology as an Enabler of Rural Health Transformation

Under the Rural Health Transformation Program, North Carolina has chosen to invest in regional networks, chronic disease care, cancer screening, maternity care, behavioral health, substance use treatment, a stable and strong workforce, and value-based, sustainable care. All of these fundamental opportunities depend on technology to enable their success.

In 2026, a meaningful rural–urban digital health gap persists in primary care. In a recent analysis of 209,152 physicians participating in the Centers for Medicare & Medicaid Services (CMS) Quality Payment Program, certified electronic health record (EHR) adoption was lower among rural physicians than urban physicians (64% versus 74%), with rural clinicians also demonstrating lower interoperability scores.17

In our own February 2026 survey of clinicians in the rural Community Care Provider Network (approximately 800 clinicians surveyed; 105 responses), only about 15% reported routinely using an AI scribe or AI clinical decision support technology. This finding suggests that, even where basic digital infrastructure is present, adoption of newer AI-enabled tools remains limited in rural practice.

The US rural provider workforce also contains a higher proportion of late-career clinicians, many of whom may have experienced prior technology implementations such as EHRs as costly, disruptive, or of uncertain value. These experiences may influence willingness or comfort with adopting new technologies, although improvements in usability and ease of integration may reduce these barriers. At the same time, the potential value of AI may be particularly significant in rural primary care, where workforce shortages, administrative burden, and limited access to specialized resources may increase the potential value of tools that reduce documentation burden or support clinical decision-making.

Importantly, the broader incorporation of technology tools remains in the early stages. A 2025 scoping review of AI in outpatient primary care found that many applications remain in developmental or early implementation stages, with relatively limited evidence of routine clinical integration.18

A separate 2025 scoping review similarly found that implementation in routine primary care was frequently constrained by usability barriers, workflow misalignment, trust concerns, financial constraints, and training needs, with the evidence base characterized by substantial heterogeneity and a predominance of small-scale feasibility studies.19

These findings underscore the importance of implementation strategies appropriately tailored to rural practice settings, including practical training, workflow integration, and attention to the resource constraints of smaller practices.

The Opportunity for AI in Rural Primary Care

First, the burden of documentation increases with the sheer volume of patients as well as with the broad range of conditions being addressed. Specialty providers often see fewer patients per day and are able to deploy standardized documentation strategies when they are evaluating and treating a narrower range of conditions. When busy clinicians use AI scribes, the ability to interact directly with patients without simultaneously needing to document the visit note allows for more focused concentration and nimbleness of thought. Providers who use AI documentation tools report substantially lower levels of burnout, while their patients report greater clinician attention and eye contact.20

Second, multiple barriers impede rural individuals from receiving specialty consultations. With few rural specialty practices, there are often considerable distances to travel and long wait times. Individuals in rural areas typically lack access to public transportation and may find the cost of fuel and lodging prohibitive. Individuals whose employment does not include sick leave may find that the loss of income associated with taking time away from work to travel to a specialty provider adds to their reluctance to seek consultation.

AI clinical decision support (CDS) tools provide information about a range of questions regarding treatment, diagnostic testing, prognosis, or causation across many common and uncommon medical conditions. In general, providers express moderate to high trust in information provided by AI-based CDS and report feeling more capable of treating a broader range of conditions.21

Systematic reviews find moderate improvement in diagnostic performance with substantial heterogeneity and limited prospective deployment, while clinician trust hinges on transparency, training, workflow fit, and validation.22,23

Lastly, the training needed to use AI scribes or CDS software can be relatively brief, and compared with implementation of an electronic health record, may require less workflow redesign. This relatively rapid ramp-up may address common reasons for hesitancy around health technology, including cost, lost productivity, unclear clinician benefit, and interference with the work of caring for patients.

Strategies for Rural AI Adoption

As the North Carolina Department of Health and Human Services begins assisting our rural clinicians in modernizing their practices and systems of care with AI technology, a number of strategies become essential.

  • Individualization. Each practice should receive recommendations based on its current level of technology infrastructure. Assessment should come first, followed by thoughtful, personalized recommendations that might include connecting to the internet and health information exchange, adopting or optimizing an EHR, and then incorporating AI tools.

  • Funding that considers the total cost of technology. This may include technical assistance, connectivity, and the administrative effort required from practice managers and clinicians. Funding should not be limited to software.

  • Broad peer adoption. Medical providers often learn best when others are changing and growing alongside them. Shared ideas and enthusiasm within regional ROOTS hubs may matter more than formal training and written materials.

  • Long-term sustainability. Providers and practices can leverage technology to improve performance in value-based practice agreements, provide a broader array of services, and capitalize on CMS programs that reimburse for improved care for individuals with complex conditions.24

Data and Health Information Exchange

An additional opportunity for AI can be found in analyzing and mining North Carolina’s increasingly robust public health and clinical data sets. Improving Health Information Exchange (HIE) connectivity and training will further increase the breadth and value of this information. These data can be used to more effectively deploy valuable resources such as community health workers, certified community behavioral health clinics, mobile cancer screening programs, and collaborative practice agreements with pharmacists and other health professionals.

Experts will need to carefully supervise and assess models deployed in rural settings that were designed and developed in urban environments. Studies show that community HIE participation can reduce duplicate testing and costs, and effective policy can pair central prioritization with local innovation.25

A Vision for Rural Health in 2031

Now, let’s return to our family doctor in 2031, five years wiser and now finding the most current medical evidence in seconds, seeing her notes well documented with far less effort, and receiving supportive, real-time data analytics that help her focus her efforts and effectively improve the health and health care experience of her patients.

We, as State Health Director and Chief Data Officer, share a vision for comprehensive transformation of rural health resting firmly on the outstanding capabilities of our healthcare workforce, the leadership talent in our communities, and the remarkable power of these revolutionary technologies.

Declaration of Interests

The authors have no conflict of interest to declare.

Correspondence

Address correspondence to Lawrence Greenblatt, 1931 Mail Service Center, Raleigh, NC 27699-1931 (larry.greenblatt@dhhs.nc.gov).