Physician-led AI: Unlocking clinical productivity in previous authorizations
Practitioners are well aware of how prior authorization disrupts the delivery of smooth, timely patient care. For those trying to do what is best for patients, this is a common cause of delays, administrative obstacles, and huge frustration. Although efforts to address these challenges have been proposed in recent years, problems remain. The number of authorizations required for daily services and treatments soared, and now each physician faces an average of 39 weekly requested exercises, further increasing their administrative burden and driving burnout.
Many of us enter medicine to help patients now face the frustrating reality of being driven away to browse manual, time-consuming processes. However, a new chapter is unfolding – increasing clinical productivity by combining the speed and change potential of AI with the judgment and supervision of experienced clinicians. The physician-led shift reimagines how previous authorizations should work and how AI supports care services.
Beyond rigid automation
The initial commitment of electronic prior authorization is to simplify the process and make faster decisions. However, such techniques often rely on rigid algorithms that cannot reflect nuances of true clinical practice. Automation alone is insufficient; physicians know that care seldom follows a predictable path. Care plans are often complex, personalized and profound nuances.
Encouragingly, this is starting to change. Based on my own experience with health programs, I see increasing efforts to bring physicians and our expertise directly into the process, building guidelines and tools that reflect clinical best practices and real-world patient needs. This means using our clinical expertise to help shape the design of AI-driven solutions.
By embedding clinician expertise directly into these tools, we are able to develop policies that guide the automation systems that will eventually be used. The result is faster approval, better clinical productivity, and care decisions consistent with the latest evidence and clinical guidelines we trust. In this approach, clinicians are not only responding to automated decisions—we are helping shape the technology that drives them.
Use physician lens to train AI
As AI adoption in healthcare, scrutiny around it has grown. But one thing is already clear: these tools require transparency and clinical supervision. This is especially true for intelligent prior authorization. AI should never be used to replace clinicians – it should support them. This is why clinical intelligence is embedded in the point of care – increasing overburden, the provider’s clinical productivity and behind the scenes in AI-supported decisions.
Physician reviews and validates guidelines and model outputs and ensures that the algorithm reflects actual, evidence-based care. In practice, this means that AI can work with providers to help handle time-consuming management tasks, surface critical data and point providers to achieve the best next step. This is a meaningful shift in a long-standing change: clinicians maintain control while getting the right support to increase efficiency and provide the best care.
This enhanced automation clinician has seen results in environmental AI: faster decision time, fewer rejections, and better provider satisfaction. For doctors, this means we can spend more time on patient care and less on paperwork.
The rise of physician-guided clinical intelligence and person-in charge AI
At the heart of this shift is a more collaborative approach, with clinically intelligent tools shaped by those who have learned first-hand about patient care. This goal is not a fully automated nursing decision-making, but a collaborative model where technology enhances clinical productivity. Our expertise defines and refines guidelines to ensure that policies are always addressed and reflect current best practices.
As a surgeon, the stakes are high. Prior authorization can delay care, lead to abandonment of treatment and cause unnecessary pain and risk. Delay in advance authorization may also lead to the patient giving up the recommended treatment altogether. But with the right tools, they all change, and these changes are obvious when we are involved in building systems that support surgeons and our team: turnover speed, less inappropriate rejection, and better consistency with medical association standards.
More importantly, these responsible AI models are not static. They are constantly refined by doctors and nurses to ensure their decision logic has a place in the real world. This means they are not only faster—they are more accurate, traceable and trustworthy. When doctors help develop these tools, automation becomes a partner, not a barrier to care and clinical productivity.
Collaborative model for improved results
Now, we see what it looks like when prior authorization becomes a collaborative effort to support care services with providers. By letting doctors shape our AI systems, we can turn leverage management into benefits for all – patients, providers and health plans.
The best performing models today are collaborative by design. They will compile clinical guidelines, get the correct data from patient records, and provide real-time approval where possible. When they can’t? They will decide to upgrade to the real clinician for review. This collaborative approach accelerates access to care while respecting clinical judgment.
These AI-driven solutions not only speed up the pace, but also help clinicians focus on what they can only do – caring for patients. This is the real clinical productivity in action, and the result is to talk to oneself.
Enhance provider satisfaction and patient outcomes
When doctors help build the tools we use in practice, prior authorization will shift from bureaucratic burden to support systems. We bring about clinical environments and nuances that are not visible to algorithms alone. The more we can participate in guiding the way these tools are built and used, the more time we will have to solve complex cases that really require our attention. That’s how we make real gains in clinical productivity and quality of care.
Call your doctor
To unlock the full potential of AI in previous authorizations, doctors must remain involved – not only users, but architects. Clinical expertise should maintain the core of AI systems creation and improvement, with the aim of automating rational medical decisions that are critical to the best outcomes and the experience of providers.
This ongoing partnership between tech developers, health plans and doctors is the right key. By rooting our AI and ML in the real world, we can shape a future where previous authorizations are smarter, faster, and better for everyone involved.
Ultimately, it’s about restoring the relationship between the doctor and the healthcare core. When previous authorizations respect clinical judgment rather than stand on its side, we can take back time and focus, and we need to focus on what is most important: our patients.
Photo: Noipho, Getty Images
Currently serving on the Medical Advisory Board of Cohere Health, Dr. Paul Johnson is an experienced orthopedic specialist who specializes in providing excellent care for patients in the Knoxville area for more than 30 years. He received his medical degree from Northwestern University and completed orthopedic residency at Vanderbilt University. Dr. Johnson then received a spinal scholarship at Emory University, furthering his expertise in spinal care.
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