Why Healthcare Data Driving Decision Intelligence Is Your Most Underused Business Asset

Every year, employers spend extraordinary amounts of money on healthcare benefits. In 2026, the average cost of employer-sponsored health coverage is projected to exceed $18,500 per employee. For a company with 500 employees, that is more than nine million dollars flowing out the door annually, often with little visibility into where it actually goes or why it keeps climbing.

What most employers do not realize is that the answer to that question is sitting right inside their own health plan. It has been there all along. The problem is that almost no one is reading it.

Healthcare claims data is the most detailed, most actionable, and most consistently ignored asset in the employer benefits ecosystem. And the employers who figure out how to use it are not just managing costs better. They are running a fundamentally different kind of organization.

The Data Exists. The Utilization Does Not.

Every time an employee visits a doctor, fills a prescription, or checks into an emergency room, a claims record is generated. That record captures diagnosis codes, provider information, treatment type, cost, and outcome. Across a workforce of any meaningful size, those records accumulate into a comprehensive picture of exactly how healthcare dollars are being spent and where inefficiencies are compounding.

A landmark scoping review published through the National Institutes of Health examined 41 employer-led studies that used employee health claims data and found that self-insured employers who engaged with this data were significantly more likely to identify high-cost utilization patterns and act on them. The research was unambiguous: access to claims data correlates directly with the willingness and ability to take cost-reducing action.

Yet for most employers, that data sits in summary form inside a report, delivered six to twelve weeks after the plan year has ended. By then, the cost has already been incurred. The trend has already set in. And leadership is left reviewing history rather than shaping it.

What Claims Data Actually Reveals

The power of healthcare claims data is not in the totals. It is in the patterns.

When analyzed at a granular level, claims data reveals which diagnoses are driving the highest spend across your workforce. It shows where out-of-network utilization is leaking cost that could have been avoided with better plan design or care steerage. It surfaces which facilities are being used most frequently and whether those facilities are delivering care efficiently or generating excessive follow-on claims. It identifies populations within your workforce who are showing early signals of high-cost conditions months before those conditions become acute and expensive.

The Employers Taking Action Already Know This

A 2025 survey conducted by the National Alliance of Healthcare Purchaser Coalitions found that employers with full access to medical and pharmacy claims data were nearly 22 percentage points more likely to take substantive action on healthcare affordability compared to those without that access. The relationship is not coincidental. When leaders can see exactly where cost is accumulating, they have both the evidence and the urgency to respond.

Those employers are not guessing at what to change at renewal. They are walking into those conversations with a specific understanding of their plan's performance, their workforce's health patterns, and the interventions most likely to generate measurable savings. That is a completely different negotiation than the one being had by employers who are relying on trend estimates and summary reports.

From Retrospective to Predictive

The next evolution of claims data utilization is not just understanding what happened. It is modeling what is likely to happen next, and that shift is what AI Decision Intelligence makes possible.

Predictive analytics built on claims data allows employers to forecast cost trajectories based on current utilization patterns, identify at-risk populations before they generate high-cost claims, and model the financial impact of plan design changes before implementation. When powered by AI Decision Intelligence, these capabilities run continuously rather than on demand, surfacing recommendations in real time rather than inside a year-end summary. AI now empowers employers to talk directly to their data in plain English, asking questions and getting answers on the spot rather than waiting on a large team of analysts to translate metrics into static, one-sided reports. Deloitte research has found that predictive analytics can reduce healthcare operational costs by as much as 15 percent when applied consistently.[1] 

The U.S. healthcare analytics market, valued at nearly $20 billion in 2025 according to MarketsandMarkets, is growing at a compound annual rate of nearly 25 percent. That growth is not being driven by academic curiosity. It is being driven by employers who have discovered that AI Decision Intelligence applied continuously to their claims data is the most reliable tool they have for managing one of their largest and most unpredictable cost centers.

The Asset You Already Own

The most important thing to understand about healthcare claims data is that you do not need to acquire it. It already belongs to you. It is being generated by your workforce every day. The only question is whether you are treating it like the strategic asset it is, or letting it collect dust in a year-end report.

Forsure's SureSystem was built on the premise that employers should not have to wait for a renewal conversation to understand what is happening inside their health plan. By connecting claims data with AI, automation, and continuous analysis, SureSystem gives HR and finance leaders the visibility they need to act on findings before they compound into a budget problem.

The data is already there. The question is what you choose to do with it.

Forsure is an AI-powered healthcare benefits platform built for employers. Learn more at forsure.ai/suresystem.

References

1.  Mercer (2025). U.S. Employers and Workers Will Face Affordability Crunch as Health Insurance Cost Is Expected to Exceed $18,500 Per Employee in 2026. https://www.mercer.com/en-us/about/newsroom/employers-and-workers-face-affordability-crunch-as-health-insurnace-cost-is-expected-to-exceed-18500-per-employee-in-2026/

2.  National Institutes of Health / PMC (2023). Scoping Review of Employer-Led Research Using Employee Health Claims Data. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611962/

3.  National Alliance of Healthcare Purchaser Coalitions (2025). Employers with Claims Data Access Take More Action on Healthcare Costs. https://www.prnewswire.com/news-releases/employers-with-claims-data-access-take-more-action-on-healthcare-costs-national-alliance-of-healthcare-purchaser-coalitions-survey-finds-302849684.html

4.  Deloitte Insights. Predictive Analytics in Healthcare: Turning Data into Actionable Intelligence. https://www2.deloitte.com/us/en/insights/industry/health-care/predictive-analytics-health-care.html

5.  MarketsandMarkets (2025). U.S. Healthcare Analytics Market Report 2025-2030. https://www.marketsandmarkets.com/Market-Reports/us-healthcare-analytics-market-135353261.html

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