Artificial intelligence is increasingly being integrated into healthcare to predict risks, monitor patients and automate administrative tasks. New research from Oklahoma State University found that rural hospitals are lagging in AI use and makes the case for investments in facilities that lack the funds to evaluate and implement it safely.
Brian Whitacre, a professor and extension economist in the university’s Department of Agricultural Economics, said he wanted to examine rural-urban differences in hospitals’ adoption, use and evaluation of predictive AI, and the factors that might make rural facilities more or less likely to adopt it.
His research paper, which is currently under peer review, uses responses from the 2023 American Hospital Association’s Information Technology Supplement. This year’s survey was the first to include questions about predictive AI model use.
Whitacre compiled submissions from 1,301 urban and 1,018 rural nonfederal acute care hospitals across the U.S. His research found that rural hospitals adopted and used predictive AI at substantially lower rates than urban hospitals, at 51% and 81%, respectively.
“The takeaway message from our paper is that the gap is real – the urban-rural gap is real,” Whitacre said.
Urban and rural hospitals adopt predictive AI for different reasons. Whitacre found that rural facilities are less likely than urban ones to use it for clinical decision-making or treatment recommendations, but equally likely to apply AI to billing and other operational tasks.
Rural hospitals are almost twice as likely to use models developed by their electronic health record provider than they are to create their own or hire a third-party developer. Urban hospitals are more likely to use third-party or self-developed models, but they still rely heavily on their electronic health record developers.
“A lot of the [electronic health records] are kind of driving the AI decision,” Whitacre said.
Rural hospitals are also more likely to use AI to identify high-risk outpatients for follow-up care.
“It makes sense that rural are actually outperforming urban on that basis, because that's where their bread and butter is,” Whitacre said. “They need that. That’s a good chunk of their revenue coming in.”
Certain factors were also linked to whether a rural hospital would adopt this technology. System membership and stronger financial health were positively associated with AI adoption.
Whitacre, for example, spoke with leadership at Mercy Hospital Ada, which is using AI to compile and share patient information, suggest possible diagnoses, analyze diagnostic imaging tests and record patient information. Dr. Benjamin Lynch, the hospital’s chief medical officer, said in a press release that they can leverage resources independent rural hospitals might lack.
Whitacre added that hospitals with higher operating margins are more likely to have extra revenue to devote toward enhancing productivity.
But the research found that critical access hospitals and facilities under for-profit or government ownership are linked to a lower likelihood of adoption.
Challenges to adoption include high upfront or per-use costs and lacking infrastructural and workforce capacity to ensure appropriate use.
The next step
The paper is just a snapshot, Whitacre said. More hospitals have likely adopted AI beyond the 2023 data he examined. His next question is, ‘Once rural hospitals do adopt AI, how does it impact their operations?’
“Does it mean they're having revenue increases? Are their patients having better outcomes?” Whitacre asked. “Or, I mean, the alternative is, are they using it super effectively, and they're not hiring as many people or even firing people? That's not really good for a rural community either.”
Whitacre currently has an open call out for rural Oklahoma hospital officials interested in collaborating on his research. He’s also spoken with leadership at Newman Memorial, a critical access hospital in Shattuck.
CEO Tom Vasko is also on the advisory board for the Coalition for Health AI, whose mission is to advance the responsible development, deployment and oversight of AI in healthcare.
He said the facility in northwest Oklahoma is currently partnering with the Mayo Clinic to provide patients with advanced cardiac remote patient monitoring. Vasko said the devices come from the Mayo Clinic and are prescribed to Newman Memorial patients. The technology helps them predict cardiac events.
The hospital also recently implemented DAX AI, which connects to their electronic health record system. It can record conversations between a provider and patient, transforming them into a clinical note that providers can verify and sign off on. This creates more direct interaction time without damaging quality of care, Vasko said.
“In rural environments, it's so important to keep interaction face to face with the provider and the patient,” Vasko said. “The patients want to feel like they're being heard. And the providers, when you talk to them, one of the reasons why they love to practice out here is that they’re like, ‘I get to have a conversation with my patient versus being behind a keyboard and typing away as they're talking.’”
Some specialists come out to Shattuck only a couple of times a month, meaning they get booked out. Vasko said this tool allows providers to see more patients, improving access to care.
The program also helps with billing by ensuring providers meet payer requirements to avoid denials.
“It's helping the bottom lines of a lot of the rural hospitals,” Vasko said.
Vasko said the hospital hasn’t quantified the difference between operations now and before it implemented these tools.
Avo, a clinical intelligence platform serving around 30 rural hospitals across the U.S., is studying the return on investment its clients experience when utilizing its AI tools. The company offers resources like an ambient AI scribe integrated into an electronic health record system and a billing optimization tool.
Laurence Coman, the company's COO and co-founder, said a critical access hospital they serve in Montana has received zero denials on the claims they submitted since launching these offerings.
“There's so much inefficiency, and back and forth between the hospitals, and then insurance,” Coman said. “[It removes] such a big headache from a critical access hospital that might have one biller, and that biller might be also doing IT work or other administrative work.”
He said he understands there are fears associated with AI’s potential to replace jobs. But he believes tools like this can help support the people working in and the finances of rural healthcare – especially amid cuts to federal Medicaid spending. Avo has calculated that AI tools for documentation and billing can help offset some of these looming losses.
“I think that's really important framing for why implementing doesn't just have to be Avo and my company's technology, but why implementing AI is more critical than ever – or really any technology that can help them with these problems,” Coman said. “It's just like a very critical juncture for rural hospitals.”
Incentivizing rural hospitals
Whitacre said the diffusion of AI into hospitals is similar to the spread of electronic health records. Research in the early 2000s documented lower adoption among rural settings compared to urban counterparts.
In 2009, the federal government set aside $27 billion through the Health Information Technology for Economic and Clinical Health Act for an incentive program to encourage hospitals and providers to adopt electronic health record systems. Billions more were allocated to help train workers and assist facilities in setting up these systems.
Whitacre argues there should be a HITECH 2.0 to support rural hospitals in adopting and evaluating AI tools.
“It's not going away. It seems like there's going to be winners, and probably the losers are going to be people that don't adopt it early,” Whitacre said. “So maybe we need to help these laggards get it up and running – find the right case studies for their hospitals. So that's what the paper hopefully makes a case for.”
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