How AI can help reduce cognitive burden

For neurologists, information overload has become a defining feature of modern practice.

Imaging reports, discharge summaries, referral records and multi-page consult notes arrive in a steady stream. Clinicians are expected to absorb it all quickly while maintaining productivity, documenting care and managing increasingly complex patient populations.

The challenge is particularly acute in neurology, where lengthy histories and extensive diagnostic documentation are routine parts of care delivery.

Those pressures are helping drive AI adoption across the specialty. According to new Doximity data, neurologists now lead physician specialists in AI adoption, with 64% reporting they use AI to help manage administrative burdens.

For healthcare CIOs and clinical leaders, that trend reflects a larger shift: AI investments are increasingly being evaluated, not only for clinical innovation, but also for their ability to reduce operational friction and clinician fatigue.

At First Choice Neurology, Florida’s largest private physician-owned neurology practice, leaders saw those challenges firsthand. The organization includes more than 100 providers across 60 locations, supports care at roughly 40 hospitals and sees approximately 1,600 patients every day.

“Due to our size and patient load, we faced many operational challenges, including navigating documentation and billing processes and the number of clicks and screens, which contributed to greater time per task and increased cognitive fatigue,” said the practice’s Dr. Ernesto Alonso.

Small inefficiencies become big problems
As organizations scale, small workflow inefficiencies can become major operational barriers.

At First Choice Neurology, paper-based patient billing slowed payment collection and increased costs. Administrative staff also managed thousands of payer-specific requirements, creating opportunities for claim denials and rework. Meanwhile, clinicians routinely navigated multiple screens and extensive documentation, simply to locate relevant patient information.

“Over time, multiple clicks, redundant navigation and delayed payments became embedded in our system,” Alonso said. “Even these seemingly small inefficiencies compounded into substantial time loss, increased administrative burden, and missed opportunities to enhance the overall patient care experience.”

The organization sought technologies that could fit directly into existing workflows, rather than forcing clinicians and staff to adopt entirely new processes. Leaders ultimately focused on AI capabilities embedded within their existing tech environment with EHR vendor eClinicalWorks.

“Our goal with implementing AI-driven systems was to simplify complex processes, eliminate unnecessary steps, and provide our clinicians and staff with real-time, actionable insights,” Alonso said.

AI built into existing workflows
One of the key deployments was the vendor’s Document AI Insights Assistant, which automatically summarizes patient records and documentation.

Rather than requiring providers to manually review every page of lengthy records, the system generates concise summaries highlighting relevant information. Clinicians and support staff use the tool while reviewing patient charts, referral documents and telephone encounters.

“Our hope was that the AI systems would streamline both clinical and financial workflows, reduce manual effort, and introduce intelligent automation across our operations,” Alonso said.

The organization also implemented healow Pay, which moved patient payments from paper statements toward digital channels. Staff can initiate payment requests through text messages and patient portal communications, allowing patients to pay through mobile wallets and other digital methods.

On the revenue cycle side, the practice deployed the eClinicalWorks Clinical Rules Engine. The platform validates claims against more than 1,400 payer-specific rules before submission, helping improve compliance and reduce manual review.

For CIOs evaluating AI initiatives, the approach highlights a common lesson emerging across healthcare: adoption tends to be strongest when technology is integrated directly into existing workflows, rather than added as a separate process.

“Having AI systems integrated across clinical and administrative workflows has helped us enhance efficiency, simplify processes, and deliver a more streamlined experience for both patients and care teams,” Alonso said.

Faster payments and fewer clicks
The most immediate financial impact came through the modernization of patient payments.

According to First Choice Neurology, healow Pay helped reduce patient accounts receivables from 27 days to 24 days. The three-day improvement generated an estimated $8,000 to $10,000 in monthly savings while accelerating cash flow.

“Patients are paying within days instead of weeks because they have several convenient payment options,” Alonso said.

The move away from paper statements also reduced mailing and printing expenses while improving convenience for patients. At scale, those operational gains created measurable financial returns.

Clinical workflows also improved.

The practice reported that Document AI Insights reduced workflow complexity by approximately nine clicks per task when creating and assigning patient documents. While a handful of clicks may appear insignificant in isolation, the cumulative effect becomes substantial across dozens of daily interactions for each provider.

More importantly, Alonso said the technology reduced cognitive burden by eliminating the need to manually review lengthy documents.

“Providers could instantly access summarized insights, enabling faster decision-making and smoother workflows,” he said. “It’s a great tool because it removes so many unnecessary steps that we’ve just had to learn to tolerate over the years.”

A CIO lesson in practical AI
The Clinical Rules Engine delivered another important outcome by helping reduce operational complexity.

According to Alonso, the platform automatically validates coding selections and payer requirements in real time, reducing reliance on staff memory and helping prevent common billing mistakes. The organization reported fewer claim errors and denials, improved first-pass claim acceptance rates and reduced rework.

The system also required little ongoing maintenance after implementation and maintained strong provider adoption by limiting alerts to situations where intervention was necessary.

That outcome is notable as healthcare organizations increasingly scrutinize AI investments for measurable business value. While much industry attention remains focused on ambient documentation, generative AI assistants and future clinical use cases, many organizations are finding their fastest returns in workflow optimization, revenue-cycle improvement and administrative automation.

For health system CIOs, CMIOs and digital leaders, First Choice Neurology’s experience underscores an emerging reality. AI does not always need to transform medicine to produce meaningful value. Sometimes the greatest impact comes from eliminating the friction that clinicians and staff have quietly accepted for years.

In an era defined by workforce pressures, documentation burdens and financial constraints, technologies that reduce clicks, accelerate payments, improve claims accuracy and lower cognitive load may prove to be among the most important AI investments healthcare organizations make. Healthcare IT News