Evolving tools: AI considerations for rural health

This year rural health leaders have a new reason to talk about artificial intelligence – most states have added an AI component to their Rural Health Transformation Program plans, including pilot programs, EHR integration, staff training, and infrastructure. This investment creates an unprecedented opportunity for rural facilities to close longstanding technology gaps.

“I always ask about the business case for a new technology like AI,” says NRHA COO Brock Slabach. “Does it solve a problem that exists in a cost-effective way without posing additional work or risk for the hospital or practitioner?”

AI in rural hospitals isn’t anything new. Since 2018, more than 2,000 hospitals across the country have used AI to identify stroke patients who needed to be transferred, helping them get lifesaving care faster. According to Andrew Ibrahim, MD, who serves as the George D. Zuidema Professor at the University of Michigan, where he practices as a general surgeon, these tools caught on because they worked well and filled a need.

“Most hospitals have these tools, and many people don’t even realize it’s AI because it’s so integrated into the workflow for stroke,” Ibrahim says. “If you are a rural hospital and there are time-sensitive services you can’t do locally, you want to be able to transfer that patient expeditiously to get them the right care. Additionally, you want to keep as much care local as you can.”

With AI becoming increasingly prevalent in rural hospitals and clinics, Ibrahim and Slabach recently identified five key considerations for rural health leaders.

Keeping care local

While AI excels at identifying patients with time-sensitive conditions who need to be sent to a larger facility, it also helps rural hospitals keep more patients local by avoiding unnecessary transfers. Ibrahim points to a recent study showing how a stroke system utilizing AI technology at approximately 45 hospitals in Kentucky managed to keep 93 percent of patients local.

“The majority of the time when a patient is having a stroke we can involve specialists at a hub and avoid transfers,” Ibrahim says. “AI tools can help rural hospitals identify more patients they can treat locally and expand the scope of their work. Rural providers will have more support through AI tools to keep patients local while treating conditions they don’t see as often. Primary care doctors will also be able to make fewer referrals and manage more patients themselves.”

Implementation has a learning curve

While many AI tools stand to benefit rural health care providers, small hospitals may initially struggle with implementation. As Ibrahim points out, integrating AI with electronic medical records takes dedicated IT staff – and typically rural hospitals cannot easily reassign people to new projects for an extended period.

“Many people have asked me what makes AI different from EHR, which was a disaster in a lot of hospitals, and the main difference is that EHR was mandated,” Ibrahim says. “AI adoption should remain voluntary – if the tools are helpful, clinicians will use them; if they’re not, they won’t. Letting clinician demand drive adoption is helpful. There’s a lot of great enthusiasm and positivity surrounding AI. Letting curiosity and demand drive it is important.”

Reducing burdensome administrative tasks

For many rural clinicians, the most overwhelming and time-consuming part of their job involves administrative tasks. When doctors must spend many hours completing paperwork not directly related to patient care, they can become exhausted and burnt out. Slabach says AI tools can help with this by summarizing charts and analyzing notes from medical appointments.

“Using ambient listening, for example, in the patient encounter with a practitioner can reduce the burden of paperwork and charting,” Slabach says. “This reduces burnout and the tedious demands of the work that drain energy and job satisfaction."

In many cases, Ibrahim adds, AI tools can save health care providers hours by reviewing complex patient information and providing a summary in a matter of minutes – and some large language models are even tailored to specific health conditions, highlighting areas where a patient may need more care or attention. This can be particularly helpful when patients have a rare type of cancer or a condition where the guidelines change frequently.

“I have a colleague in Montana who told me the days he doesn’t want to do this anymore are not the days he works long hours,” Ibrahim says. “It’s when he has to do stuff like paperwork, scheduling, coordinating, and faxing forms. I think offloading a lot of these administrative tasks and keeping clinicians doing clinical care will be impactful.

Recruiting and retaining workforce

Rural health care has a longstanding workforce shortage, with some providers choosing to practice in urban or suburban settings because they worry about the professional isolation of a small-town practice. Here Ibrahim raises another positive: The same AI benefits that reduce burnout and help with staff retention can also attract additional workforce. Tools that aid productivity, planning, and continuing education can help hospitals and clinics recruit and retain staff while freeing clinicians up to spend more time with patients.

“I finished medical school 15 years ago, and if you ask me something outside of what I do day to day, I would be very rusty,” says Ibrahim. “AI tools and clinical decision support can boost the clinicians' knowledge base and help them feel confident that they can provide state-of-the-art care. It would be a huge morale boost.”

Discerning needs can be challenging

Another potential concern is the sheer volume of AI tools that exist. “It’s probably better for most rural hospitals to consider their needs and find tools that address those specific needs,” says Ibrahim, who also serves as chief clinical officer at Viz.ai, a firm aiming to help transform care coordination and improve patient outcomes. “Otherwise they might end up only using a fraction of the tools.”

That’s why Viz.ai is working with NRHA to develop a toolkit to help rural hospitals focus on their greatest needs and vet potential vendors. The toolkit will be available to NRHA members this fall and will include questions for hospital leaders to ask vendors to help them avoid surprises, manage cybersecurity concerns, and more.

“AI has come on the scene relatively quickly,” Slabach says. “Testing products and their claims is a priority for rural facilities. On the flip side, AI technology can offer solutions that were unthinkable five years ago. I’m hopeful about the opportunity to keep patients local longer and reduce practitioner burnout.”

Ibrahim has also heard from many rural health leaders who are excited about the technology and “want all the bells and whistles,” but he cautions against this approach.

“There is a little due diligence to figure out what’s a good AI tool and what’s not, what’s a trusted vendor and what’s not,” he says. “They’re not all the same.”

This is part one of an ongoing series looking at emerging rural health technologies.

Gain more guidance with NRHA in KC

Your chance to learn more about the role of AI in rural health care directly from the experts is at NRHA's Rural Health Clinic and Critical Access Hospital Conferences Sept. 15-18 in Kansas City, Mo.

Sessions will discuss the roles of AI vs. expertise, how to integrate AI tools into a rural hospital strategic plan, ROI from denial prevention AI at two Colorado CAHs, and much more.

Register by Aug. 25 to save hundreds on our fastest-growing events.