Todd Doze, CEO of Janus Health
Photo: Janus Health
Hospitals are losing millions every year to a hidden but fixable problem: referrals that never get scheduled. Patient referrals can stall because of administrative bottlenecks, leading to both lost revenue and delayed care.
Todd Doze, CEO of Janus Health, which develops technology for the healthcare revenue cycle, believes artificial intelligence can unlock new capacity in hospital operations by automating intake, clinical review and treatment validation – helping solve problems with referrals, which he calls one of the biggest blind spots in hospital revenue cycles.
We spoke with Doze to gain his expert views on this blind spot, the role AI can play in solving revenue cycle challenges, and how some health systems already are seeing financial and patient care benefits.
Q. Why do you believe referrals are one of the biggest blind spots in hospital revenue cycles?
A. Referrals are one of those operational gray areas even the most advanced health systems struggle to manage effectively. It's not that organizations are overlooking referrals. It's largely due to the fact that operational and technological infrastructures supporting them were never designed to track, measure and optimize this end-to-end process.
What begins as clinical intent quickly turns into a fragmented administrative workflow built on outdated technology, disconnected systems and manual handoffs.
Between order entry, insurance verification, prior authorization, scheduling and patient communication, there are countless opportunities for delay, rework or revenue loss. This negatively impacts both financial and team performance through missed appointments, unconverted referrals and revenue leakage that most health systems can't quantify because they lack the operational intelligence to see where the breakdowns occur.
Health systems need to be able to identify where patients drop out of the process, or how much revenue never materializes due to administrative friction. Without transparency around referral volume, conversion rates or leakage by specialty, executives are forced to make decisions in a vacuum.
In my opinion, the real consequence isn't financial, it's clinical. Every delayed or lost referral represents a patient whose health journey was interrupted by administrative complexity. And until we modernize this process, we can't truly say we're delivering on the promise of connected, coordinated, patient-centered care.
Q. What role can AI play in reducing manual work, increasing conversion rates and streamlining access with this referrals challenge? And what might this signal for the future of healthcare operations?
A. AI is starting to make a real impact on the referral process in healthcare, and it's doing it in a way that reduces manual work, increases conversion rates and speeds up access. One of the most exciting trends right now is the use of generative AI agents in revenue cycle workflows.
These agents can adapt to changing conditions, make decisions where a human normally would, and automate tasks that used to require clinical knowledge or specialized experience. That's especially important because revenue cycle management teams are shrinking, labor costs are rising, and the demand for accurate, timely referrals isn't slowing down.
The most exciting thing about AI is its ability to learn and improve over time. These agents get better with every transaction, absorbing more data and refining their decisions along the way. That means they don't just replicate human work – they can actually help teams work smarter, handling repetitive or complex tasks more efficiently and freeing human staff to focus on higher-value work.
This is a practical, hands-on way AI can increase conversion rates and accelerate access for patients.
Looking ahead, AI has the potential to fix what has traditionally been a fragmented and opaque process. It can give health systems full visibility across the patient journey, close the loop with the ordering physician and keep patient care in network.
We'll see better coordination across departments and locations, fewer dropped or delayed referrals, and a smoother experience for the patient. When the system works this way, everyone benefits, patients get timely care, clinicians can focus on treatment rather than paperwork, and health systems can operate more efficiently and confidently.
Q. How are some health systems already seeing financial and patient care benefits in the area of referrals improvement?
A. Health systems are starting to see encouraging financial and patient care benefits from improvements in referral management. For example, at one large academic system, automation was used to handle the clinical input required for referrals in radiology.
Previously, 24 clinicians were dedicated to this work every day. Within a few months, over half of those clinicians were able to return to direct patient care, freeing staff for higher-value work and supporting better patient outcomes.
In another health system, a largely fax-based referral process had been underestimating weekly volumes because not all orders were making it into the EHR. After implementing automated intake and routing, the system was able to capture and process nearly three times as many orders.
Even in the first few months, this has translated into increased revenue, faster patient access, more efficient scheduling and much greater visibility into referral workflows.
Across multiple early implementations, health systems are also gaining better visibility into operational details, such as who is managing each referral, the urgency or clinical sensitivity of orders, referral volumes and outcomes, and time spent versus time saved.
Having this level of insight into referral workflows has proven to be a game changer, with tangible impacts on operational efficiency, workflow optimization and patient care.
Follow Bill's health IT coverage on LinkedIn: Bill Siwicki
Email him: bsiwicki@himss.org
Healthcare IT News is a HIMSS Media publication.
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