Claims data is useful. But it is late.
Every employer knows the pattern. Costs look stable, the renewal arrives, and a handful of large claims drives the increase. By the time a health problem shows up in claims data, the expensive part has usually already happened.
A person can look inexpensive on paper and still be moving in the wrong direction clinically. They may have a condition that is being managed poorly, or not at all. That doesn't appear in a claims report until it becomes a hospitalization, a surgery, or a new diagnosis.
Most cost-containment strategies are built on that late data. They negotiate the price of care that has already become necessary. Our model works earlier. We identify the people whose trajectory can still be changed, before rising risk becomes a rising claim.
Just 10% of your people drive 80% of your spend.
The problem: every year, that 10% changes.
Identifying next year's high-cost claimants is the key to preventing exploding costs.
They are in your population right now. Most of them look fine in this year's claims data. The employers who bend their cost trend are the ones who can find and activate those people while their trajectory can still be changed.
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That is what Converging Health is built to do. How we do it:
Identify. Activate. Measure.
Identify
Finding tomorrow's high-cost claimants today
Traditional risk models are built primarily on past claims and diagnosis codes. That makes them good at explaining money that has already been spent, and much weaker at telling you whose spending is about to change.
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The Whole Person Risk Score™ (WPRS™) was built to answer the second question. Instead of relying on claims alone, it integrates three distinct dimensions of risk into a single, interpretable score for every member of your population. Together, these dimensions connect the person, the care they are receiving, and their ability to act on it. That is what Whole Person means in practice: a structurally wider view of risk than claims alone can provide.
1.
Absolute Risk
The underlying clinical picture: diagnoses, disease stage, medications, clinical complexity, biometrics, demographics, and social factors. How sick is this person today?
2.
Flare Risk
Dynamic instability: the likelihood that a person's condition escalates into acute utilization. Two people with the same diagnosis can carry very different flare risk depending on engagement, adherence, behavior patterns, and their relationship with primary care. How likely is this person's condition to escalate?
3.
Care Quality Risk
Gaps between the care a person should be receiving and the care they are actually getting: missed guideline-based care, incomplete care pathways, poor sequencing, and prevention that never happened. Is the care itself quietly falling short?
Score a population on risk, not just cost, and it splits into four very different groups. Here is what that looks like in practice:
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UPPER RIGHT QUADRANT: For members already generating significant spend, the work is coordination: the right care, in the right sequence, at the right site, with someone making sure the pathway holds together.
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UPPER LEFT QUADRANT: The accidents and sudden events that no model predicts. This quadrant is why insurance exists. It is also, as the data shows, a far smaller share of spend than most employers assume.
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LOWER RIGHT QUADRANT: This is the quadrant where the most preventable cost lives, and it is where our model concentrates its effort. These members are inexpensive today and on a trajectory not to be. Reached early, their path can still bend.
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LOWER LEFT QUADRANT: Most of your population. The goal is simply to keep the healthy healthy: prevention, primary care relationships, and easy access when something changes.
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UPPER RIGHT QUADRANT: This quadrant confirms what you already know: a small group of high-risk members drives the overwhelming majority of spend.
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UPPER LEFT QUADRANT: Only a sliver of spend comes from low-risk people who got hit by something no one could have predicted. Most high cost is not random. It is visible in the risk data before it arrives in the claims data.
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LOWER RIGHT QUADRANT: These members barely register in a claims report today. But they carry the same risk profile as the people in the expensive quadrant above them. This is where next year's high-cost claimants come from, and a claims-based view cannot see them at all, because they have not generated the claims yet.
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LOWER LEFT QUADRANT: These are healthy members. The goal is to migrate members to this quadrant.
Activate
Better health decisions with human support.
MyPHA connects members with a Personal Health Assistant (PHA): a real person who helps them navigate healthcare, use their benefits, coordinate care, and follow through on the steps that can improve their health.
WPRS identifies which members are rising in risk, as well as specific, actionable opportunities to reduce risk. Across a typical employer population, that adds up to thousands of concrete opportunities.
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Analytics alone would leave that list sitting in a report. Our model assigns it to a dedicated Personal Health Assistant (PHA): a named healthcare professional with a direct phone number.
The relationship starts with proactive outreach. PHAs do not wait for members to raise their hand, because the members who most need help almost never do. Using motivational interviewing, the PHA works to understand each member's "why": what actually matters to them, what has kept them from acting, and what would make change stick. That understanding, combined with the member's data, becomes a personal action plan.
The members driving your costs are busy, often feel fine, and find healthcare confusing. A trusted person who calls them, knows their situation, and removes the obstacles is the key to preventing avoidable cost escalation.
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Activation is where the model's financial results are generated. Risk intelligence tells us where to aim. The Personal Health Assistant is how the trajectory actually bends.
MyPHA works alongside the member
01
Getting the right care
Finding high-quality doctors, scheduling appointments, transferring medical records, and arranging second opinions before major procedures.
02
Rebuilding the primary care relationship
For members managing chronic conditions through the emergency room, or through no one at all, the single highest-value move is often reconnecting them with a primary care physician who quarterbacks everything else.
03
Guiding stage-appropriate care
Our care pathways match intervention to disease stage, so a back problem gets physical therapy before it gets a surgical consult, and a complex diagnosis gets a center of excellence instead of the nearest available option.
04
Closing the gaps the score identified
Screenings, follow-up visits, lab work, medication adherence, condition education. Each closed gap moves the member's risk score, so progress is visible, not assumed.
05
Making the benefits work
Resolving billing and insurance issues, coordinating benefits, and connecting members to programs they are already paying for but never knew existed.
06
Staying accountable
Ongoing coaching, check-ins, and follow-up. The PHA is the one person in the member's health life whose job is to make sure things actually happen.
Measure
How you'll know it's working, and how it gets better
Measurement does two jobs in our model. It proves what happened, in dollars, on your own population. And it tells us what to do differently next quarter. The first job is why you'll trust the results. The second is why year three saves more than year one.
Raw cost comparisons hide the truth. A population's spend can fall because care improved, or because sick members left the plan. It can rise because care failed, or because a wave of high-risk new hires arrived.
To separate performance from population mix, we measure something sharper: cost per point of risk. Divide what a population spends by the total risk it carries and you get a number that behaves like a fuel gauge for your health plan. When care gets more effective, cost per risk point falls, even if total spend moves around for other reasons. When members drift, it climbs.
Every quarter of data makes the next quarter smarter
A risk score is a snapshot. Measurement is what keeps it current, and what turns a static analysis into a system that improves. Four things change as the data comes in:
1. Who gets reached next?
Risk scores refresh continuously. Members who improved free up capacity. Members who slipped, and new hires who arrive already carrying risk, move up the outreach list. The work concentrates wherever the next dollar of prevention returns the most, and that target moves every quarter.
2. Which interventions get repeated?
We can see which approaches actually closed gaps and lowered risk, and for which conditions. Outreach that works gets standardized across the population. Outreach that didn't gets replaced. Your Personal Health Assistants get better at your specific population, not a generic one.
3. Which programs are earning their keep?
Most employers are paying for several health programs at once: a diabetes program, an MSK app, a mental health benefit, a weight management vendor. We can measure risk and cost movement for the members actually using each one. That tells you which are producing change, which need better member steerage, and which are worth cutting. Held to the same standard we hold ourselves to.
4. How the benefit plan is designed.
Risk migration responds to plan design. When the data shows members avoiding primary care because of cost, or filling prescriptions inconsistently, or landing in the emergency room for problems primary care should have caught, that points to specific, fixable benefit decisions ahead of the next plan year.