See employer, member, geographic, competitive, and healthcare signals in one place instead of reconciling separate reports from separate teams.
Get a plain language read of where to grow, depend, or intervene, with the evidence behind each call, not another dashboard to interpret.
Move before your expansion or AEP deadline without a data-science bench or a 12- to 24- month build.
Health plans currently make high-stakes decisions about market expansion, employer growth, network coverage, and Medicare strategy with data spread across disconnected reports, systems, and teams. We bring those signals together so payer teams can see where opportunities are strongest, where risks are emerging, and what to do next.
Powered by SignalFuse™, that intelligence becomes a clear, decision-ready view teams can act on without building the analytics themselves.
See the member and household makeup behind each employer group, so you know who to pursue, how to price the risk, and how to win the RFP.
Prioritize markets by growth opportunity, affordability, competitive pressure and network coverage, down to ZIP3, county and metro.
See where populations are aging into Medicare, how those populations differ by market, and where the opportunity supports county, entry, expansion and bid-year planning.
Bring employer, member, geographic, competitive, and healthcare intelligence together so teams can see where growth opportunity is strongest, which employer groups or markets to prioritize, where network or competitive risk is increasing, and what action to take next.
We don’t give you another dashboard to interpret. Teams get a plain-language read they can take straight into growth, account planning, underwriting, and network conversations.
Built for payer use cases without exposing member-level information. Data is linked and analyzed at the employer, geographic and segment level, not the individual level, so PII and PHI never enter the picture.
The methodology behind Data Axle for Healthcare has been reviewed by our healthcare data partner—the builder of one of the most comprehensive de-identified healthcare data foundations ever assembled—confirming that it meets the bar for using this data while remaining HIPAA- and privacy-compliant.
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