The $1 Million Question: Can You Predict Your Next High-Cost Claimant Before They Cost You?

The Bottom line: Segal's 2026 Health Plan Cost Trend Survey confirms what CFOs and benefits leaders already suspect – high-cost claims are accelerating, becoming more unpredictable, and traditional cost-containment strategies aren't keeping pace. This aligns with broader employer benefits research from the Kaiser Family Foundation, which shows that health benefit costs continue to outpace wage growth and general inflation year after year.

The real breakthrough isn't just identifying who's expensive today. It's predicting who will become expensive tomorrow and intervening before costs spiral.

The Acceleration Problem: High-Cost Claims Are Outpacing Everything Else

Segal's latest research reveals a troubling trend: the frequency and severity of catastrophic health claims continue to climb at rates that outpace general medical trend, with high-cost claimants driving costs at unprecedented rates. For employers and health plans managing risk, this isn't just a budget problem. It's a predictability problem.

According to Segal's analysis of 3.9 million members across 882 employer groups, high-cost claimants – defined as individuals whose annual claims exceed $100,000 – now represent a disproportionate share of total medical spend. Independent claims analysis from the Health Care Cost Institute corroborates this trend, showing that catastrophic claims are not only increasing in frequency but also in severity, with average costs per high-cost claimant climbing faster than overall medical trend.  

While only approximately 1% of an employer's health plan members have annual claims higher than $100,000, they account for 33% of total spend. The Milliman Medical Index provides additional context on per capita healthcare costs, highlighting how concentrated spending among a small population drives the majority of employer and health plan financial risk. And the trajectory is worsening.

The traditional approach has been reactive: Wait until someone crosses the high-cost threshold, then manage the case retrospectively through intensive care coordination, specialty pharmacy interventions, or stop-loss reinsurance. But by the time someone hits $100,000 in annual claims, the clinical cascade is already underway. Hospitalizations have occurred. Complications have set in. Chronic conditions have progressed to acute episodes.

What if you could see it coming six months earlier? As benefits consultants like Mercer and Aon have documented in their employer health plan surveys, the organizations achieving the best cost outcomes are those investing in predictive analytics and early intervention strategies.

From Identification to Prediction: The AI Advantage

Segal's survey makes clear that understanding who is high-cost today is table stakes. The competitive advantage lies in predicting who will become high-cost tomorrow, and intervening with precision before costs bloom.

This is where advanced analytics diverge from traditional claims reporting. HIMSS research on AI in healthcare underscores the distinction: legacy analytics describe what happened, while machine learning models predict what will happen and prescribe interventions to change outcomes.  

Most benefits dashboards can tell you who spent $150,000 last year. Fewer can tell you who is on track to spend $150,000 this year. Almost none can tell you which seemingly healthy members are six to twelve months away from becoming catastrophic claimants, and what interventions could change that trajectory.

Solera's Precision Insights^TM Suite was built for this exact challenge. By layering proprietary AI and machine learning models on top of real-time claims data, Precision Insights doesn't just flag who's expensive. It identifies the early warning signals, clinical patterns, and cost acceleration curves that indicate someone is on a path toward high-cost status, often before traditional risk scoring models catch it.

How Rising Risk Prediction Works with Precision Insights

Precision Intercept^TM analyzes claims patterns, pharmacy fills, provider visit frequency, comorbidity clusters, and utilization trends to identify members at elevated risk of cost escalation. These aren't members who are already expensive. These are members whose data signatures suggest they're becoming expensive.

The model flags:

• Pre-diabetics with emerging cardiovascular markers who are 6-12 months from a cardiac event (clinical research from organizations like the American Diabetes Association and the American Heart Association demonstrates that early intervention in these populations can dramatically reduce both progression rates and associated costs).

• Behavioral health patients with prescription adherence gaps trending toward crisis hospitalization

• Cancer survivors with unmanaged pain or depression at risk of secondary complications

• Chronic condition patients missing preventive touchpoints likely to decompensate

Precision Navigate^TM then routes these high-risk individuals into appropriate, evidence-based digital and physical health interventions before clinical events occur. This isn't generic wellness outreach. It's targeted, condition-specific engagement designed to change the cost curve before it spikes.

The Economic Case: Intervention Costs vs. Crisis Costs

Segal's data underscores the financial stakes. When a member crosses into high-cost territory, the economic damage is severe and often sustained over multiple years. But the cost of preventing that escalation is a fraction of the cost of managing it after the fact.

Consider the math. These cost ranges are consistent with data from the American Heart Association on cardiovascular event expenses and the National Institute of Mental Health on behavioral health crisis costs, both of which highlight the extreme cost disparity between crisis care and preventive intervention.

• Average cost of a cardiac event: $75,000-$150,000 (acute episode, not including ongoing management)

• Average cost of a 12-week digital cardiac rehabilitation program: $300-$800 per participant

• Average cost of behavioral health crisis hospitalization: $10,000-$30,000 per admission

• Average cost of a digital behavioral health intervention: $200-$600 per participant

The ROI isn't just favorable. It's transformational. But only if you intervene before the crisis. The CDC's chronic disease prevention initiatives emphasize this same principle at the population level: the most cost-effective healthcare strategy is preventing costly conditions from developing or escalating in the first place.

Traditional care management waits for the $100,000 claim to trigger a case management referral. Predictive intervention catches the $5,000 claimant who's trending toward $100,000 and redirects them into a $500 digital health program that changes the outcome entirely.

Why Prediction Requires More Than a Dashboard

Segal's findings make another critical point: not all high-cost claimants are created equal. Some are predictable and preventable. Others are not. The challenge is distinguishing between the two and allocating resources accordingly.

A cancer diagnosis in a previously healthy 40-year-old may be clinically unpredictable. But the diabetic with three missed endocrinology appointments, irregular A1C testing, and recent antibiotic fills for recurrent infections? That's a cost bloomer you can see coming.

Generic predictive models often conflate the two, generating noise and alert fatigue. Sophisticated models differentiate between catastrophic unpredictability (where intervention won't change the trajectory) and preventable escalation (where early action has measurable impact). Healthcare technology evaluators like KLAS Research have identified this differentiation capability as a critical vendor selection criterion, noting that not all predictive analytics platforms deliver actionable intelligence with demonstrated outcomes.

Solera's Precision Insights Suite is trained on 2B+ million claims and outcomes data from across our Digital Health Network. The models learn not just who becomes expensive, but the specific clinical conditions driving that escalation – enabling targeted, condition-specific intervention rather than generic wellness outreach. This isn't theoretical prediction. It's validated, real-world performance data. IQVIA's research on digital therapeutics and outcomes-based interventions supports this approach, demonstrating that evidence-based digital health programs can produce measurable clinical and financial returns when properly targeted to high-risk populations.

Integration Is the Difference Between Insight and Impact

Predictive analytics are only valuable if they connect to action. Predictive analytics are only valuable if they connect to action. Segal's survey highlights the operational challenge many employers and health plans face: even when they identify rising-risk individuals, connecting them to the right resources at the right time remains a manual, fragmented process.  

Rock Health's digital health adoption research consistently finds that integration challenges—not technology limitations—are the primary barrier preventing employers and health plans from realizing value from digital health investments.

This is where Solera's integrated ecosystem delivers differentiation. Precision Insights doesn't just flag risk. It can be coupled with automated workflows that:

1. Route members to clinically appropriate digital health programs via the Solera Digital Health Platform

2. Facilitate seamless enrollment with minimal friction

3. Track engagement and outcomes in real time

4. Adjust interventions based on member response and clinical progress

5. Bill through medical claims with transparent cost and outcome tracking

The result is a closed-loop system where predictive intelligence drives intervention, intervention drives engagement, and engagement drives measurable cost avoidance. No spreadsheets. No manual outreach campaigns. No hoping someone calls the EAP number.

Accountability Is the New ROI Standard

Segal's research arrives at a moment when CFOs and benefits leaders are demanding more than projections. This accountability shift mirrors broader healthcare payment transformation, as evidenced by CMS Innovation Center's expansion of alternative payment models that tie reimbursement to outcomes rather than volume.  

They want proof. They want accountability. And they want vendors who are willing to align financial incentives with outcomes. The Business Group on Health's annual employer survey consistently shows that large employers are prioritizing vendors who offer performance guarantees and transparent, claims-based outcome measurement.

Solera's model is built on this principle. Our Digital Health Network partners operate under outcomes-based contracts. Our Precision Insights Suite doesn't just predict risk—it measures whether interventions actually reduced that risk. And our claims-based billing model ensures that every dollar spent on digital health is visible, measurable, and tied to medical cost impact.

For health plans and employers using Solera, the question isn't just "Who will be expensive?" It's "Did we prevent them from becoming expensive, and can we prove it?"

That's the accountability standard Segal’s report is calling for. And it's the standard Solera is already delivering.

The Shift from Reaction to Prevention

High-cost claimants will always exist. But the percentage of those claims that are preventable is larger than most organizations realize. Federal health initiatives like the HHS Healthy People framework estimate that a significant portion of chronic disease burden — and associated costs — could be prevented or delayed through early identification and evidence-based intervention.  

Segal's 2026 survey makes clear that the acceleration in catastrophic claims isn't inevitable. It's a failure of prediction and early intervention.

The organizations that will contain costs over the next decade aren't the ones with the best stop-loss insurance or the most aggressive utilization review. They're the ones who can see around corners, predict escalation before it happens, and intervene with precision.

Solera's Precision Insights Suite is that predictive engine. It's not a reporting tool. It's an intervention platform. And for health plans and employers looking to change the cost curve before claims spiral, it's the difference between managing crises and preventing them.

Ready to Move from Hindsight to Foresight?

If Segal's findings resonate with your own claims data, let's talk about what predictive intervention looks like in practice. Solera's Precision Insights Suite is already helping health plans and employers identify cost bloomers months before they escalate and connect them to evidence-based digital health interventions that change outcomes.

Let's make the invisible visible — and the preventable, prevented.

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