Small and Rural Practices Risk Being Left Behind in the Digital Revolution
The promise is tantalizing: artificial intelligence that can streamline one of healthcare’s most frustrating administrative burdens. One large national insurer reported that use of an AI tool made the prior authorization process 1,400 times faster. Yet beneath these impressive statistics lies a more complex reality that could reshape the healthcare landscape in unexpected ways.
The Prior Authorization Problem
Prior authorization has evolved from a cost-control mechanism into what many physicians describe as one of their greatest administrative nightmares. The process, designed to ensure medical necessity and control costs, now consumes enormous amounts of physician time and delays patient care across the country.
The numbers tell the story of a system under strain. Practices spend countless hours navigating insurer requirements, tracking down documentation, and managing delays that can negatively impact patient outcomes. Delayed chemotherapy infusions, postponed joint replacements and abandoned insulin starts have turned PA into a national access issue.
The AI Solution Promise
Artificial intelligence appears to offer a lifeline. AI is revolutionizing prior authorization in healthcare by automating data submission, enhancing decision support, enabling real-time authorization, and improving communication. The technology can integrate with electronic health records, match clinical data against payer criteria, and generate documentation in real time.
AI offers the potential to reduce the time and cost associated with prior authorizations. And as regulations continue to push for greater transparency and speed in the process, many in the industry believe AI will play a critical role in helping practices adapt.
The regulatory landscape is pushing toward this digital future. The rule requires payers to implement, by Jan. 1, 2027, a “Prior Authorization Application Programming Interface” (API) to streamline the PA process. For example, the API requires impacted payers to send PA decisions to providers within 72 hours for expedited (i.e., urgent) requests.
The Dark Side of Automation
However, the AI revolution in prior authorization isn’t unfolding as smoothly as proponents hoped. According to a 2024 Senate committee report, health insurers’ use of AI tools has led to higher rates of care denials, sometimes 16 times higher than typical. This raises ethical concerns about potential inappropriate denials of necessary care.
The American Medical Association has raised serious concerns about AI implementation. “Using AI-enabled tools to automatically deny more and more needed care is not the reform of prior authorization physicians and patients are calling for,” said Dr. Scott.
Critics warn that, without transparency and human oversight, artificial intelligence may simply speed up denials rather than streamline access. This concern highlights a fundamental tension: while AI can make processes faster, it doesn’t necessarily make them fairer or more patient-centered.
The Digital Divide in Healthcare
Perhaps the most concerning aspect of the AI prior authorization revolution is how it might exacerbate existing inequalities in healthcare. Small practices and rural healthcare systems face unique challenges in adopting these technologies.
Rural hospitals, smaller systems and health clinics without a massive IT infrastructure should reach out to AI companies to discuss potential partnerships, said Graham Walker, co-director of advanced development at Kaiser Permanente’s medical group. But reaching out and actually implementing are two different challenges entirely.
Health systems are deploying AI to ease documentation and billing burdens, and to provide better patient care. Rural organizations and independent or community hospitals are no exception, despite challenging circumstances. Yet these challenging circumstances—limited IT budgets, smaller staff, outdated infrastructure—create significant barriers to AI adoption.
The Resource Gap
The reality is that AI implementation requires substantial resources that many smaller practices simply don’t have. Large health systems can afford dedicated IT departments, AI specialists, and the infrastructure needed to integrate complex AI tools with existing electronic health record systems. Small practices often operate on tight margins with minimal administrative staff.
This creates a potential two-tier system where large, well-funded practices benefit from AI-streamlined prior authorization processes, while smaller practices continue to struggle with manual, time-intensive procedures. Some doctors are turning to generative artificial intelligence to streamline the prior authorization process and “operate at the same level as companies that have essentially infinite resources.”
Regulatory Pressure and Implementation Challenges
The CMS Interoperability and Prior Authorization Final Rule, finalized in January 2024, aims to streamline the PA process, improve transparency, and ensure that decisions are based on individualized patient circumstances. The rule mandates that AI and other automated tools can assist in utilization.
While these regulations push the industry toward AI adoption, they don’t address the fundamental capacity issues facing smaller practices. The deadline-driven nature of regulatory compliance can force practices to adopt suboptimal solutions or fall behind entirely.
The Human Element
Despite technological advances, the human element remains crucial in prior authorization decisions. AI has the capability to extract pertinent and relevant information from clinical records for the prior authorization process. However, clinical decision-making often involves nuances and patient-specific factors that current AI systems may miss.
The concern isn’t just about technological capability—it’s about ensuring that AI tools enhance rather than replace clinical judgment. When AI systems are designed primarily for efficiency rather than clinical appropriateness, they risk undermining the quality of patient care.
Bridging the Gap
The challenge moving forward is ensuring that AI benefits all practices, not just those with the resources to implement cutting-edge systems. Healthcare payers recognize prior authorization as a core administrative process that’s ripe for improvement with artificial intelligence. But this improvement must be inclusive.
Potential solutions include:
Collaborative Partnerships: Rural hospitals, smaller systems and health clinics without a massive IT infrastructure should reach out to AI companies to discuss potential partnerships. These partnerships could provide access to AI tools without requiring massive upfront investments.
Standardized Solutions: Rather than custom AI implementations, the industry needs standardized, plug-and-play solutions that smaller practices can easily adopt and integrate with existing systems.
Financial Support: Regulatory bodies and payers should consider providing financial assistance or incentives to help smaller practices implement AI tools, similar to meaningful use incentives for electronic health records.
Training and Support: AI adoption isn’t just about technology—it’s about ensuring healthcare workers have the skills and support needed to use these tools effectively.
The Stakes
The stakes couldn’t be higher. If AI prior authorization tools become the standard but remain accessible only to well-funded practices, we risk creating a healthcare system where administrative efficiency correlates with practice size and resources. This could worsen health disparities and limit patient access to care.
Artificial Intelligence (AI) may enhance access to primary health care in rural settings, especially in areas with an underserved and rural populace, due to systemic challenges in infrastructure inadequacies, shortages of trained professionals, and poor preventive measures. But realizing this potential requires intentional effort to bridge the digital divide.
The AI revolution in prior authorization is already underway. The question isn’t whether it will transform healthcare administration—it’s whether that transformation will benefit all patients or only those served by well-resourced practices. As the industry moves forward, ensuring equitable access to AI tools may be just as important as the technology itself.
The promise of AI in prior authorization is real, but so are the risks of leaving smaller practices behind. The healthcare system’s response to this challenge will determine whether AI becomes a tool for improving care across all settings or another factor driving disparities in American healthcare.
Sources
- Oliver Wyman. “Unlocking The Potential Of AI In Prior Authorization.” September 2024.
- Holland & Knight. “Regulation of AI in Healthcare Utilization Management and Prior Authorization Increases.” October 2024.
- Thoughtful AI. “How AI is Revolutionizing Prior Authorization in Healthcare.” January 10, 2025.
- Medical Economics. “Prior authorization: How it evolved, why it burdens physicians and patients, and the promise of AI.” April 24, 2025.
- Advisory Board. “How doctors are using AI to save time on prior authorization.” July 16, 2024.
- PCG Software. “2024-2025 AI Prior Authorizations Outlook.” August 12, 2024.
- American Medical Association. “How AI is leading to more prior authorization denials.” March 10, 2025.
- Healthcare Dive. “How rural hospitals, Silicon Valley can head off the AI digital divide.” March 4, 2025.
- HealthTech Magazine. “How Can Rural Healthcare Organizations Benefit From AI?” June 20, 2025.
- ScienceDirect. “Artificial intelligence for access to primary healthcare in rural settings.” December 15, 2024.
Discover more from Doctor Trusted
Subscribe to get the latest posts sent to your email.
