Stop Patching Symptoms. Start Fixing Provider Data.
For decades, the healthcare industry has treated provider data like a leaky pipe. We wrap it in tape, place a bucket underneath, and hope it holds until the next quarter. But patching the symptoms with annual clean-ups and manual updates will never achieve true network adequacy.
To fix the core of your provider network, you need to understand exactly where and why the architecture is failing.
What you’ll learn
Soon, Candor Health will publish a comprehensive study examining the true accuracy of provider directories. We bypassed the surface-level symptoms to test actual payer networks directly against health-system directory data.
By reserving your copy of the study, you will discover:
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The Frequency of False Data
A deep dive into a new metric that measures exactly how often payer networks over-include providers or retain stale addresses.
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The Cost of Misalignment
How the disconnect between health plans, providers, and government registries creates operational friction and compliance risks.
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The Path to a Single Source of Truth
Actionable steps to stop relying on static snapshots and start managing a dynamic, trustworthy network.
Sign up now, and we will send the Provider Accuracy Study directly to your inbox the moment it is available.
Why provider data keeps breaking
Through our work with leading health systems and payers, we have identified four structural root causes behind provider-directory failure. The upcoming study will show you the measurable impact of each.
Fragmented sources
Health plans, hospitals, and government registries maintain separate records that refuse to communicate.
Self-reported data
Relying on busy providers and office managers to manually update their information creates a massive, unsustainable administrative burden.
Infrequent refresh cycles
Managing a dynamic network with quarterly or annual static snapshots means data is obsolete the moment it goes live.
No validation layer
Without automated validation to verify practice locations and days claimed, bad data simply overwrites good data.
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