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Four Takeaways for Smarter Provider Data Systems

Provider data accuracy has moved from operational nuisance to regulatory and reputational priority. In a recent Fierce Healthcare webinar, Candor Health, CertifyOS, and Oscar Health examined what it actually takes to build provider data infrastructure that holds up under current compliance demands and member expectations.

One theme ran through the entire conversation: accuracy and infrastructure have to evolve together.

Sury Agarwal
Sury Agarwal
· 3 mins read · November 2025
Four Takeaways for Smarter Provider Data Systems
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Key Takeaways
  • 1 New regulations including the Real Health Provider Act introduce civil penalties for provider directory inaccuracies, raising the compliance stakes beyond periodic audits.
  • 2 A single data change — an address update, a network status shift — can ripple through claims, directories, and adequacy reports simultaneously.
  • 3 Provider groups and payers often have misaligned incentives around data quality, contributing to ghost networks and chronic roster inaccuracies.
  • 4 AI-dependent workflows are only as reliable as the underlying data layer. Governance and structure matter more than tooling.
  • 5 Scalable provider data systems depend on interoperability, intelligent survivorship logic, and real-time change management — not just better validation.

Accuracy Is Now a Regulatory and Reputational Imperative

In a recent Fierce Healthcare webinar with CertifyOS and Oscar Health, one central truth surfaced across every discussion: provider data accuracy and modern infrastructure must be solved together. The two problems reinforce each other — and neither can wait.

For years, provider directory inaccuracies were treated as an operational inconvenience. Regulatory pressure has changed that calculus.

Candor Health CEO Sury Agarwal framed the stakes directly: “The No Surprises Act required directory updates every 90 days, but the Real Health Provider Act takes it further with civil penalties for inaccuracies.”

CMS now allows Medicare Advantage members to switch plans mid-year when directories are found to be inaccurate — a provision that translates directory errors into direct membership exposure.

Mitch Gorodokin, Senior Vice President of Business Development at CertifyOS, added a structural caution that applies regardless of how much automation a health plan deploys.

No amount of automation or AI will make your data accurate if it is not structured and governed properly.

Mitch Gorodokin
CertifyOS

The Data Problem Is Structural, Not Just Technical

Provider data doesn't fail because health plans lack tools. It fails because the same data moves through multiple organizations — payers, MSOs, delegated groups — each operating on different definitions, formats, and update schedules.

An address should just be an address, but it's not.

Jennifer Dougherty-Gallagher
Oscar Health

That structural fragmentation means a single change propagates unevenly. Agarwal described the core challenge: “Even if accurate data exists somewhere, maintaining and distributing it across systems is incredibly hard without the right infrastructure in place.”

Ownership is part of the answer. Health plans cannot assume clean data will arrive from delegated groups or provider organizations.

“We cannot rely solely on delegate or provider groups to send us clean rosters,” Agarwal noted. “We need proactive monitoring, validation, and enrichment of the data ourselves.”

Accuracy has to be embedded into workflows — not applied as a downstream correction.


Fragmented Incentives and the Ghost Network Problem

One of the more difficult dynamics in provider data management is that the organizations contributing data don't always share the same priorities around accuracy. Provider groups have operational reasons to over-list providers. Payers absorb the compliance and member experience consequences.

The result is ghost networks: directory listings that don't reflect actual network availability, frustrating members and drawing regulatory scrutiny.

The panel's view was that intelligent validation infrastructure and unified data governance can help realign those incentives. When data integrity becomes a shared operational standard rather than each party's internal problem, the network-level benefits compound.

As Agarwal observed, “Accuracy, efficiency, and member experience can move in the same direction when incentives are aligned.”


What Future-Ready Provider Data Infrastructure Looks Like

The panel converged on a clear picture of what scalable, interoperable provider data management requires:

  • National visibility into provider practice locations and network overlaps

  • National visibility into provider practice locations and network overlaps

  • Infrastructure capable of supporting directories, referrals, and claims simultaneously

  • Intelligent survivorship logic that resolves conflicting records and establishes a single source of truth

No amount of automation or AI will make your data accurate if it is not structured and governed properly.

Mitch Gorodokin
CertifyOS

AI Depends on the Integrity of the Data Layer

The AI dimension matters here too. Downstream workflows — from claims routing to member-facing directories to network analytics — increasingly depend on AI-assisted processing. But those workflows inherit whatever data quality exists at the foundation.

Agarwal was direct: “AI is only as effective as the data feeding it. Stability at the data layer is essential.”

Why This Matters
We cannot rely solely on delegate or provider groups to send us clean rosters. We need proactive monitoring, validation, and enrichment of the data ourselves.

Frequently Asked Questions
Q
What is the Real Health Provider Act?
A
The Real Health Provider Act introduces civil penalties for provider directory inaccuracies, going beyond the 90-day update requirement established under the No Surprises Act. It raises the compliance threshold for health plan provider data management.
Q
What is a ghost newtork?
A
A ghost network is a health plan provider directory that lists physicians or facilities that are not actually available to members. They form through over-listing, outdated data, and the absence of validation between what is listed and what is real.
Q
Why do ghost networks persist despite compliance requirements?
A
Ghost networks typically result from misaligned incentives between provider groups and payers, where over-listing providers serves short-term operational purposes for contributing organizations while payers bear the compliance and member experience consequences.
Q
What is survivorship logic in provider data management?
A
In practice, survivorship logic determines which provider record becomes authoritative when multiple systems disagree. It is a core part of maintaining a reliable provider data foundation across multiple systems and sources.
Q
Why isn't better validation sufficient to fix provider data quality?
A
Validation corrects errors after they enter operational systems. Many inaccuracies originate during ingestion, when incoming roster files from multiple organizations with different formats and update schedules are first processed.
Ready to fix provider data at the source?

Standardize provider roster ingestion, reduce reconciliation overhead, and improve provider directory reliability with Candor Health.

Sury Agarwal
Written by
Sury Agarwal
Chief Executive Officer

Sury Agarwal is on a mission to transform how healthcare organizations access, manage, and trust provider data. Candor’s AI-powered platform supports payers, digital health companies, and provider groups with care navigation, referral management, network strategy, and regulatory compliance. Sury brings 12+ years of experience tackling complex data challenges. Previously, he was VP of Engineering and part of the founding team at Moat, which was acquired by Oracle for $850M in 2017. He is a Cornell University graduate.

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