To bend the healthcare cost curve, brokers and employers need to embrace predictive intelligence and proactive decision-making.
In this setting, being proactive means tapping into all the healthcare data available to understand a group's composition before cost is incurred. Public pricing data, claims, pharmacy and demographic signals are all important to create a highly specific view of each group. It's not just about identifying a high-cost claimant after the fact; it's all about understanding what a member is likely to need and ensuring the plan design and network actually support that. From there, you can create a true healthcare strategy.
At a recent Crumdale Specialty seminar, Ria Shah, Handl Health co-founder and chief product officer, explained that while healthcare pricing MRFs are a foundational piece of the infrastructure, it’s really about how you enrich and execute on that information that will truly create lasting change. You can't just look at one data set to figure out how to lower plan costs.
Take utilization as an example. Cost drivers are not uniform. A manufacturing group's biggest exposure might be MSK and site-of-care. A tech company might see specialty pharmacy and mental health as their biggest drivers. Negotiated rates tell you what a network costs structurally, but claims and demographic data are needed to tell you what this group is likely to use. Put those together and you can build a plan that actually fits, she explained.
The healthcare industry needs “to be more intentional and reviewing data on a more frequent cadence to be able to drive insights and act on them,” Ria told the audience.
Employers are the strongest at retrospective analysis; after all, everyone has at least some claims reporting. The improvement needs to happen in the predictive space. Most employers aren't using rate benchmarking data to project what a network will cost before they're locked in. That gap is closing fast. The data exists now to do real personalization at the group level, but most employers just haven't been shown what's possible.
And in the rush to bring AI into every aspect of the industry, it’s important to not fall for the hype. AI has been extremely helpful in cleaning data and recognizing information patterns, she said, but it should be used as an augmentation tool, not a replacement for every aspect of health plan management.
“There are some deeply human touch points that are required,” she said, mentioning care steerage. “You’re going to want to talk to a human for certain parts of the experience.”
Shah said she hears a common refrain from employers and consultants all the time: “We know that there are some areas we want to dig into, we want to make these changes, but we don’t know where to begin and how to see it all the way through so it produces the results that we want.”
Understanding how the plan is performing currently, along with the top handful of high-cost providers, is the first step, she said. It’s also important to clearly state the objectives for any new plan design. Then it’s about designing, deploying and continuously optimizing the plan.
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