ICHRA's Next Stage Of Maturity Pairs Plan Choice With Integrated Navigation

ICHRAs have moved from novelty to mainstream cost-management strategy fast enough that the ecosystem around them is still catching up. Employers have figured out the funding mechanics, and employees are increasingly choosing from a meaningful set of options rather than a single group offering. The harder question is what happens once that choice is on the table. The opportunity in front of benefits leaders is to build the navigation layer that turns plan choice into plan fit.

Leading the charge toward this new kind of healthcare ecosystem is Murat Alpman, Chief Innovation Officer at healthcare data analytics firm HealthCorum. The Boston-based company builds provider quality scores, price transparency, and patient-provider matching tools into a unified API used by health plans, self-funded employers, and benefits technology partners. Alpman has spent the last decade in healthcare technology after thirty years across tech startups. His vantage point on the data layer shapes how he reads the next phase of ICHRA adoption.

"More choice doesn't automatically produce better outcomes. In fact, for many employees, more choice creates confusion. They're making one of the most important financial decisions of the year with a limited understanding of networks, deductibles, formularies, provider access, and total cost of care," he says. In his view, ICHRA's success in its next stage depends on whether the choices it creates are paired with the guidance employees need to use them well.

The selection problem is bigger than the list

The standard ICHRA selection experience puts a list of plans in front of an employee and treats the selection as a self-service exercise. The risk Alpman identifies is that the people most likely to need guidance, employees with chronic conditions or families with specialized care needs, are the same people most likely to mismatch their plan to their situation. "A healthy 25-year-old and a family managing diabetes should not receive the same guidance. What's happening is that sometimes employees select the wrong plan, or even worse, they get confused and just postpone the decision entirely."

The downstream cost of a mismatched plan compounds across the year. Out-of-network care, surprise specialist costs, and providers who turn out not to participate after enrollment all stem from selection decisions made without the right information at the right moment. "ICHRA's funding mechanism is the vehicle, but without navigation, many people won't know which route to take. The value comes from getting employees to the right destination efficiently." That framing reorients what an effective ICHRA platform layer needs to deliver. The list of plans is the starting point. The decision support around the list is the product.

What an integrated navigation layer looks like

The convergence Alpman describes pulls together five capabilities that most ICHRA implementations currently split across different vendors: plan selection guidance, provider quality data, price transparency, network adequacy for the employee's existing providers, and AI-powered support that operates on the employee's phone. "It's a single platform that not only has the list of available networks, but also the information about what each network means for you. If I'm diabetic, which network is the best for my condition? If I switch networks, what does it mean for my existing providers? How much does an average episode cost in this network versus that one?" These are the questions, he says, that current solutions fail to answer clearly.

The same logic extends to provider-level decisions inside the chosen plan. Once an employee has selected coverage, the navigation must continue through specialist selection, procedure cost estimation, and facility comparison. "Maybe I have six options for cardiologists," Alpman says. "Who has more experience in the procedure I'm looking for, and what is the quality? How much do they charge, and how about the facilities?" That continuity between plan choice and provider choice matters because the moment of plan selection and the moment of care are typically months apart. An employee who picks a plan in November but does not understand which surgeon to choose in March has not actually received the value the funding mechanism was supposed to enable.

Fragmentation is the operational enemy

Alpman is direct that the technology required to build this stack exists. The barrier is that most vendors solve only one piece of the puzzle, leaving the employee to assemble the rest across multiple platforms. "Some vendors want to help the call centers. Some want to help the brokers. Nobody is looking at the whole picture. But at the end of the day, the member needs all three things: the list of options, the guidance to choose between them, and the help to navigate providers."

Fragmentation also fails on access. The ICHRA workforce often includes part-time employees, hourly workers, and people managing multiple jobs, who are not going to log into five different platforms with five different credentials to navigate their benefits. "The access needs to be very easy. It needs to be available on the phone," he asserts. "Fragmentation is only going to make things more expensive, cause confusion, and delay care. The last thing we want is for the member to give up and say, 'I cannot navigate this thing.'"

The support is in the numbers

The economics of building the navigation layer become viable when AI handles the volume of routine guidance and call centers stay reserved for the genuinely complex cases. Alpman's working assumption is that an AI navigation layer can resolve roughly 80% of common selection and provider questions, with the remaining 20% routed to care navigators. "At the end, it all boils down to the money. When they have proper guidance, your employees are going to make fewer calls to the expensive call centers. The member is happy, the outcome is better, and the total expense is lower."

The cost equation works because routine plan-comparison and provider-lookup questions are exactly the kind of structured queries AI handles well, particularly when the underlying data already exists in quality and price form. The expensive human-led navigation gets reserved for the cases that actually require it.

Success lies in outcomes, not enrollment

Alpman believes the definition of ICHRA success has to evolve with the model itself. Enrollment volume was the right metric for the first wave, when the operational question was whether employees could move from group plans into individual coverage at all. The second wave requires a sharper benchmark. "The success for version 2.0 is the employees selecting the appropriate coverage, accessing care effectively, and achieving better health and financial outcomes," he says.

The constructive read on Alpman's argument is that ICHRA is delivering on its original promise, and that the next phase is about extending the model into the experience layer where outcomes are actually decided. The employers who build or partner for that integrated navigation layer now will produce measurably better results for their workforce. The ones who stop at the funding mechanism will see employee confusion compound into worse plans, delayed care, and higher costs across the year. "Choice without guidance creates confusion," Alpman says. "The next phase of ICHRA innovation is transforming that choice into confidence."