Why Self-Funded Health Plans and Good Data Go Hand in Hand

There's a moment in every self-funded health plan conversation where the employer pauses and asks a very reasonable question:

"How will I know if this is actually working?"

It's not a challenge. It's not skepticism. It's what any smart business decision-maker asks before taking on something new. They want to see numbers, trends, and a way to track whether the plan is delivering what was promised.

Having good data ready for that moment can help the conversation go a lot more smoothly.

The Self-Funded Shift Is Already Happening

The landscape has changed significantly. According to the 2025 KFF Employer Health Benefits Survey, 67% of covered workers in the U.S. are now enrolled in self-funded health plans. Among large firms, that number reaches 80%. And even among smaller employers (10 to 199 workers), over half are now in either self-funded or level-funded arrangements.

A big part of what's driving this shift is cost. Annual premiums for family coverage reached $26,993 in 2025, up 24% over five years. For many employers, the fully insured model has become harder to justify, especially when it offers limited visibility into how those dollars are being spent.

Self-funding offers a different approach. Instead of paying a fixed premium to a carrier, self-funded employers pay claims directly. They get access to their own data, more control over plan design, and the ability to customize benefits based on what their employees actually need.

That said, having access to data and actually using it well are two different things. And that's where analytics comes in.

The Question Every Employer Asks

Here's how a typical self-funded health plan conversation goes. The broker or TPA walks the employer through the financial model (stop-loss thresholds, PEPM costs, expected claims liability). The employer follows along. The numbers make sense on paper.

But then comes the follow-up:

"Once we're in this, how do I track whether it's working? What does the reporting look like? How do I know my employees are actually getting healthier?"

It's a fair question, and one that deserves a strong answer. Employers are used to getting very little visibility from fully insured plans. When they're considering self-funding, they want to know that this time will be different.

The answer usually isn't just one thing. It's a combination of tools and capabilities working together:

• Employer reporting that shows the financial picture
• Engagement and utilization data that reveals how the plan is being used
• Chronic care coordination that tracks how ongoing conditions are managed
• Patient outcome metrics that measure real health improvement
• Cost savings analysis that ties it all back to dollars

Each of these serves a different purpose, and together they give employers the full picture they're asking for.

The Different Pieces of Self-Fund Analytics

When an employer self-funds, they're taking on financial responsibility for their employees' healthcare. For a company with 200 employees, that can mean managing over $2 million in annual health spend. It's a meaningful commitment, and it's natural for employers to want tools that help them stay informed across multiple dimensions.

Self-fund analytics is a set of metrics that each answer different questions. Here's how they tend to break down:

Engagement and Utilization Tracking

Engagement and utilization tracking answers a different question: are employees actually using the benefits available to them?

If the plan includes direct primary care or a clinic benefit, are people taking advantage of it?

Understanding utilization patterns helps employers see whether the plan is gaining traction and where there might be gaps in awareness or access.

Cost Savings Analysis

Cost savings analysis goes deeper into the financial picture than employer reporting alone. It looks at specific areas where the plan is reducing spend compared to the prior model or industry benchmarks.

How are ER visit rates trending? What about avoidable hospitalizations or generic drug substitution rates?

This is the data that helps employers quantify the return on their decision to self-fund.

Chronic Care Coordination

Chronic care coordination focuses on how ongoing health conditions are being managed across the employee population.

Chronic conditions like diabetes, hypertension, and behavioral health issues tend to drive a significant share of claims spend. According to AHRQ's Medical Expenditure Panel Survey, roughly 20% of individuals account for about 80% of healthcare spending.

Tracking whether patients with chronic conditions are engaged in care plans, adhering to treatment, and seeing clinical improvement can be one of the most impactful things a self-funded employer monitors.

Patient Outcomes

Patient outcomes look at the health side of the equation. Beyond cost, employers also care about whether the plan is helping their people get healthier.

Trends in clinical markers like HbA1c levels, blood pressure management, and preventive screening rates help paint a more complete picture of how the plan is performing on the health front.

Each of these capabilities tells a different part of the story.

• Employer reporting shows the financial view
• Engagement data shows adoption
• Chronic care coordination shows care management
• Patient outcomes show health impact
• Cost savings tie it all together

Having access to these layers gives employers clarity as they navigate their self-funded plan.

How This Shapes the Conversation

Let's go back to that employer sitting across the table. They've heard the self-funded pitch. They're interested but cautious, which is completely understandable.

Now imagine being able to walk them through each of these layers.

You start with the employer report: here's how the plan performed last quarter financially.

Then you show engagement data: here's how utilization is tracking across primary care, specialist visits, and preventive services.

Then chronic care: here's how employees managing diabetes are doing in their care plans.

Then outcomes: here are the clinical trends.

Then cost savings: here's where the plan is saving money compared to where you were.

That kind of layered visibility can really shift the conversation.

Instead of asking the employer to trust a projection, you're showing them what self-funded employer analytics looks like when it's set up well. Each piece answers a different concern, and together they build a complete picture.

HealthCompiler brings together employer reporting, engagement and utilization tracking, chronic care coordination, patient outcomes, and cost savings into one connected platform. It integrates with EHR systems, claims data, and wellness platforms, giving self-funded employers and care teams a consolidated view across all of these dimensions.

The Data Integration Challenge

One of the practical challenges in self-funded analytics is that the data for each of these capabilities often lives in different places.

• Claims data is in one system
• EHR data in another
• Eligibility files come from the TPA
• Pharmacy data sits with the PBM

Employer reporting needs claims and eligibility data. Chronic care coordination needs clinical data from EHRs. Patient outcomes need both. Getting all of that to work together isn't always straightforward.

This is where having an integrated analytics platform can be particularly helpful.

A system that pulls from multiple sources, normalizes the data, and presents it in a way that makes sense to both clinical teams and finance leaders solves a real operational problem.

It's the kind of technical challenge that companies like HealthCompiler have focused on, building integrations with Athena, Elation, Cerbo, eClinicalWorks, Hint, Epic, and other major EHR platforms to ensure that employer reporting, care coordination, and outcomes data all draw from the same connected foundation.

When the data comes together, each piece of the analytics picture becomes more complete.

• The employer report is more accurate because it reflects real utilization
• Chronic care coordination is more effective because it's informed by clinical data
• Cost savings analysis is more credible because it's backed by outcomes

Everything reinforces everything else.

Why This Matters Across Employer Sizes

Self-funding is no longer limited to large corporations.

The 2025 KFF data shows that self-funding is growing across the board. Level-funded arrangements, which combine a self-funded structure with stop-loss protection, now cover 37% of workers at firms with 10 to 199 employees.

Regardless of whether an employer has 50 employees or 5,000, the underlying questions tend to be the same:

• How is the plan performing?
• Are employees engaged?
• Where is the money going?

The way each organization approaches those questions may look different, but the desire for clear, accessible answers is universal.

Making the full range of self-funded analytics, from employer reporting to patient outcomes, available across different employer sizes is something the industry continues to work on.

Having visibility into cost, engagement, care coordination, and health outcomes can help any employer feel more confident in how their plan is performing.

The Advisor's Opportunity

For brokers, consultants, and TPAs working with self-funded employers, having a comprehensive analytics offering can be a meaningful differentiator.

The employers exploring self-funded plans today tend to be well-informed buyers. They understand the potential savings. What they're often looking for is a partner who can help them track results across multiple dimensions, not just cost.

Being able to walk into a meeting and show the full picture:

• Employer reporting for the financial view
• Engagement data for adoption
• Chronic care tracking for care management
• Outcome metrics for health impact
• Cost savings for the bottom line

adds another layer of confidence to the conversation.

It shows the employer that you're thinking about ongoing visibility, not just the initial setup.

When an employer asks "what's in it for me?", having data-driven answers ready across each of these areas doesn't just help move the conversation forward. It helps build a long-term relationship built on transparency and trust.

The Bottom Line

Self-funded health plans already offer real advantages on their own in terms of cost control, flexibility, and data ownership.

Analytics simply helps employers see those advantages more clearly, track how things are going, and make adjustments along the way.

More often than not, the conversation between "I'm interested in self-funding" and "I'm ready to move forward" comes down to whether the data is there to support the decision.

HealthCompiler is helping to make that part a little easier.