Navigating the Shift to Bulk Data and AI

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Navigating the Shift to Bulk Data and AI

From NPPES to NPD the changes coming to MA plan finder and other provider data requirements

Gene Vestel

Jun 01, 2026

Ron Urwongse, co-founder of Defacto Health, and I sit down to break down the rapid shifts hitting CMS regulations, the transition from standard FHIR APIs to national bulk data datasets, and how agentic AI workflows are compressing engineering timelines from months to an afternoon.

Listen now on YouTube, Spotify, and Apple Podcasts.

We discuss:

The Bulk Data Pivot: Why CMS is expanding beyond endpoint APIs into massive bulk NDJSON files for Medicare Advantage plans.
The National Provider Directory Ecosystem: A technical audit of the new data release, where it shines, and where the logical models are still failing.
AI as an Engineering Accelerator: How teams are using agentic workflows (like Claude Code) to build production-ready validation engines overnight.
Smart Scheduling Links: The inevitable roadmap toward universal, consumer-centric open appointment booking.
The CMS Feedback Loop: Why the newly established CMS Health Tech Ecosystem Slack channel is radically altering how regulations are refined in real time.

My 3 Biggest Takeaways

1. Compliance cycles have compressed from six months to a single weekend

In the legacy enterprise playbook, updating a platform to conform with newly dropped technical implementation guides took a quarter or more of roadmap planning. Today, that layout is dead. Ron noted that when CMS dropped updated technical guidance on a Friday afternoon, multiple forward-thinking payers had already fully conformed by Monday morning.

The differentiator isn’t engineering headcount; it’s the shift toward AI accelerators. If your senior architects aren’t actively feeding CMS Implementation Guides into tools like Claude Code to interpret, write, and deploy schemas, you are building an operational bottleneck.

2. We are transitioning from simple Master Data Management to Federated Graphs

The industry has long clamored for CMS to run a centralized database as a mastered system of record. Instead, the tactical reality looks much more like a federated graph across hundreds of independent nodes. CMS isn’t attempting top-down data cleansing; they are supplying the network scaffolding to link provider organizations, practitioners, endpoints, and digital footprints. Payers must now prioritize internal accuracy auditing because upcoming mandates like the Real Health Providers Act will require plans to publicly score and publish the validity of their directory data.

3. Open scheduling is the ultimate bottleneck for value-based care

Up to 75% of open care gaps remain unfilled simply because of the high friction involved in patient engagement such as transcribing an identical medical history onto a 40-page clipboard during an intake cycle. Universalizing lightweight specifications like Smart Scheduling Links originally built to aggregate vaccine availability during COVID will allow insurance directories to natively embed real-time booking slots. The monetization model still needs guardrails to protect providers from high platform fees and patient acquisition gaming, but opening up EHR scheduling data to the wider ecosystem is an absolute necessity to drive actual consumerism in healthcare.

Deep Dive: Auditing the National Provider Directory

The launch of the National Provider Directory marked a major milestone for healthcare data liquidity, but looking under the hood reveals clear technical hurdles that the developer community is currently solving.

       [ Practitioner ]
               │
     Is associated with
               ▼
   [ Provider Organization ] ──  Publishes  ──► [ Bulk NDJSON Dataset ]
               │                                         │
       Resolves endpoint to                              │ Contains
               ▼                                         ▼
   [ Patient-Centric Endpoint ] ◄──  Audited by  ── [ AINPI.dev Engine ]

The Architectural Gaps in the NPD Release

To test the real-world utility of the new data, Gene imported the entire publicly available directory into an open-source tool built over a weekend to evaluate and audit conformance: AINPI.dev. The audit highlighted several distinct areas where the logical models require iteration:

Endpoint Association Confusion: There remains an ongoing architectural debate within CMS working groups regarding where endpoints should sit logically. Attaching a FHIR connection endpoint directly to an individual practitioner creates massive, unmanageable data duplication. The correct semantic approach maps endpoints strictly to the Provider Organization, which then establishes relationships down to the underlying practitioners.
The Specialty Taxonomy Mess: There is still no clean, unified consensus on processing specialty codes. Payers are left navigating multiple conflicting sources of truth published across PECOS, NPPES, and specialized CMS charts, leading to distinct fragmentation in search results.
Missing Endpoints: The front door to patient-directed data access relies on clean endpoint visibility. Currently, a vast percentage of active provider organizations feature zero mapped digital endpoints, making true interoperability a fragmented experience depending entirely on where a patient lives.