CMS’ Health Tech Ecosystem: Promise, Power, and the Fine Print

I'm a health data scientist who works on systems modeling, AI integration, and policy infrastructure - so when CMS announced its new Health Tech Ecosystem initiative on July 30, I paid attention. The headlines were big: a voluntary collaboration with tech giants like Amazon, Google, Epic, and OpenAI to create a “modern digital health ecosystem.” But I wanted to understand what that actually meant. What, exactly, are these companies committing to? What’s in CMS’s interoperability “blueprint”? And how does this compare to past efforts to fix the plumbing of American health data?

This piece reflects what I found after reading through the technical documentation behind the initiative. Some parts of it are genuinely promising. Others raise thorny questions about feasibility, governance, and whether voluntary alignment can overcome the deep fragmentation of the current system.

CMS Launches Voluntary Health Data Ecosystem with Tech Giants

In July 2025, CMS announced a new partnership with some of the biggest names in tech -Amazon, Google, OpenAI, and others. The effort is part of what the agency is calling its Health Tech Ecosystem Initiative, a voluntary program meant to modernize how health data moves through the system, especially for Medicare and Medicaid.

The idea, according to CMS, is to build a “patient-centric” digital ecosystem where data can flow more easily and securely. Instead of rolling out new regulations, they’re inviting healthcare and tech companies to work together on shared goals: real-time data exchange, better interoperability, and smarter tools that can support care delivery-many of them powered by AI.

CMS has been clear that this isn’t a mandate. They’re framing it as a movement-one built on collaboration, not compliance. What that collaboration actually looks like in practice remains to be seen, especially given that the business models and incentives of some of these tech companies often run counter to what many in the health community would consider responsible or ethical use of AI.

The Persistent Problems This Initiative Claims to Solve

For those of us who’ve been mired in the realities of health IT, announcements like this are more than press releases - they’re potential inflection points. Over the years, I’ve seen how deeply the plumbing matters:

• Patient consent is often fragmented or inconsistently honored, leaving providers uncertain about what they can share and patients unsure about who has access to their data.

• EHR interoperability remains painfully shallow - even systems using the same vendor often can’t exchange a complete patient record without manual intervention.

• Unstructured data piles up in PDFs, faxes, and scanned images, making it unusable for analytics or automated decision support.

• Duplicate records and mismatched patient identities undermine data integrity, creating safety risks and administrative headaches.

• Inconsistent coding standards (LOINC for labs, RxNorm for meds, SNOMED for diagnoses) prevent clean aggregation and comparison of data across systems.

These aren’t abstract issues - they shape real patient experiences and create friction in everyday clinical workflows. That’s why this initiative caught my attention. If CMS and its tech partners can deliver on even part of this vision, it could address problems that have lingered for decades. But the devil here isn’t in the technology - it’s in the adoption, the governance, and whether the incentives are aligned well enough to sustain the work.

How the CMS Aligned Network Would Actually Work

The beating heart of this initiative is the concept of the CMS Aligned Network - a national, voluntary club of health data networks, EHRs, providers, payers, and patient-facing apps that all agree to a shared set of interoperability rules. CMS’ pitch is simple: if everyone plays by the same open, standards-based criteria, we can finally make real-time, secure, patient-authorized health data exchange work at scale.

Once a network meets the criteria in the CMS Interoperability Framework, it can call itself “CMS Aligned” - a kind of public badge signaling to patients, providers, and other participants that it’s safe, standards-compliant, and ready to share data seamlessly across the ecosystem. From there, each stakeholder group has its own set of commitments to keep the whole system functioning.

On paper, it’s an elegant design. Below is how the requirements break down - first in the technical language CMS uses, then in plain terms for how they might play out in the real world.

1. CMS Aligned Networks

• Implement the CMS Interoperability Framework, including clinical and claims data.

• Support FHIR APIs (US Core IG, USCDI v3 or later) by July 4, 2026, with full terminology compliance (LOINC, RxNorm, SNOMED).

• Enable bulk FHIR data exchange and real-time encounter notifications.

• Provide chart notes and clinical documents in both human- and machine-readable formats.

• Offer network-wide record search and maintain a CMS-approved security certification (e.g., HITRUST).

Plainly put: This is the backbone of the ecosystem - a nationwide, standards-driven network that can move health data quickly and securely, no matter where it’s stored. In theory, this means a patient’s lab results from a rural clinic could be in front of an ER doctor in another state within seconds.

2. EHR Vendors

• Make structured and unstructured patient data accessible to CMS Aligned Networks.

• Deliver encounter notifications within 24 hours.

• Accept and return patient data via QR code, Smart Health Card, or Smart Health Links without requiring separate portal logins (if IAL2/AAL2 verified).

Plainly put: This would break down one of the biggest walls in healthcare - the closed systems run by EHR companies. If vendors comply, switching doctors or health systems wouldn’t mean starting from scratch with your medical history.

3. Providers

• Join CMS Aligned Networks to make patient records discoverable across care settings.

• Support real-time access to records for treatment and patient use.

• Return all available patient information when legally permissible and identity-verified.

Plainly put: Doctors, hospitals, and clinics would all be connected to the same core data-sharing system. That means fewer delays when referring patients, fewer redundant tests, and less risk of dangerous gaps in information.

4. Payers

• Join or form a CMS Aligned Network and share claims data.

• Respond to requests from patients, providers, and other payers.

• Query and retrieve relevant clinical data tied to recent claims.

Plainly put: Health insurers would have to open up their records, making it easier for patients and providers to see a full picture of care and costs. That transparency could also help catch billing errors or fraud faster.

5. Patient-Facing Apps

• Integrate with CMS Aligned Networks, using CMS-approved identity verification.

• Support use cases like “Kill the Clipboard” (digital insurance cards, FHIR visit summaries), AI assistants for care planning and chronic disease management, and diabetes/obesity prevention tools.

• Participate in CMS review processes and follow HIPAA rules where applicable.

Plainly put: This is where patients would feel the change most directly. Apps could pull in all your records in one place, help you check symptoms or manage chronic conditions, and let you share your information instantly with new providers.

Enforcement

There are no direct penalties. Compliance is based on self-attestation, potential review if concerns arise, public scorecards, and adherence to existing laws like HIPAA.

Plainly put: There’s no real “stick” here - CMS is betting that transparency, peer pressure, and shared incentives will be enough to get everyone to play along.

Why Voluntary Compliance May Not Be Enough

While the Health Tech Ecosystem may read like a checklist of long-overdue upgrades, the reality is far messier. Much of what CMS lays out is technically feasible, even desirable - but the actual implementation depends on voluntary participation, economic alignment, and trust in systems that, frankly, haven’t earned it yet.

These are some of the fault lines that risk undermining the promise of the initiative:

1. The Economics Don't Add Up for Early Adopters

CMS is betting big on voluntary alignment. But the financial math doesn’t add up for many players - especially early adopters.

Implementing FHIR APIs, real-time encounter notifications, and robust identity verification isn’t cheap. Unlike earlier federal efforts like Meaningful Use, there’s no guaranteed reimbursement or incentive funding. That means networks and providers are expected to take on substantial infrastructure costs without a clear return on investment.

Worse, organizations that go first risk footing the bill while their competitors wait to see if the initiative gains traction. It’s a classic prisoner’s dilemma - and CMS is hoping goodwill and momentum will win out over cautious bottom lines.

2. Legacy Systems Aren't Ready for Real-Time Data Exchange

The CMS Interoperability Framework assumes a level of technical readiness that simply doesn’t exist across much of the healthcare landscape.

Many health systems are still struggling to meet basic interoperability requirements from prior regulations. Adding support for FHIR-based real-time notifications, document exchange, and federated record search requires architectural changes that most legacy EHRs weren’t designed for.

Health Information Exchanges (HIEs), often seen as the “glue” for data sharing, operate on infrastructure that’s years out of date - and often optimized for batch queries, not the real-time, patient-directed requests CMS is now emphasizing.

Even where systems can technically comply, data quality remains a silent killer: clinical records often lack proper coding, or use homegrown terminologies that defy automated mapping. Fancy APIs won’t fix garbage in/garbage out.

3. Digital Identity Requirements May Exclude Vulnerable Populations

CMS requires participants to adopt IAL2/AAL2 identity verification - think mobile driver’s licenses and passkeys - to enable seamless access to sensitive health data. That’s a noble goal, but it runs headfirst into digital reality.

The populations most in need of this kind of system - Medicare beneficiaries, rural patients, people with lower digital literacy - are the least likely to have the technology, connectivity, or confidence to use digital identity tools.

And on the provider side, front-desk workflows aren’t ready for this. The idea that a patient will flash a QR code or Smart Health Card at check-in sounds great until you realize most clinical staff haven’t been trained on these tools, and their EHRs don’t support ingesting that data smoothly.

Instead of streamlining access, these requirements could inadvertently increase friction - or worse, widen the gap between the digitally connected and the digitally excluded.

4. Tech Companies' Business Models Conflict with Data Sharing

If this initiative seems bold, it’s because it threatens to reshape entire business models - and not everyone is thrilled about that.

Payers have long treated claims data as competitive intelligence. Being asked to “freely share” it with other payers or providers “when appropriate” sounds collaborative, but in practice it cuts against proprietary analytics and actuarial advantage.

EHR vendors, too, are famously reluctant to open their systems. Their entire value proposition has been built around walled gardens, bespoke integrations, and charging for every additional connection. True interoperability-especially if enforced via open APIs-undermines that business logic.

And the CMS Aligned Networks themselves? They’re being asked to do quite a bit (identity verification, directory maintenance, encounter alerts, record locator services) without any clear revenue model. Unless CMS provides some sort of funding or incentive structure, these networks will either collapse or quietly commercialize access to stay afloat.

5. Who's Liable When AI-Powered Health Apps Get It Wrong?

The framework nods to AI-driven apps and conversational assistants - tools that interpret full clinical records, offer symptom advice, and guide chronic disease management. But nowhere is it clear: who’s liable when the AI gets it wrong?

If a patient makes a medical decision based on incomplete or incorrect information pulled from a CMS Aligned Network, and an AI assistant fails to flag the risk - who’s on the hook? The provider? The app developer? The network itself?

There are also questions about data accuracy. If records are pulled from multiple networks, and those records contradict each other or contain outdated information, who’s responsible for correcting them? There’s an unspoken assumption that more data equals better data - but without governance, you just end up with a larger pile of inconsistencies.

The framework invokes HIPAA but leaves large parts of the liability chain unspoken. And when you’re dealing with real-time, AI-driven health decisions, ambiguity isn’t just a legal problem - it’s a patient safety one.

6. Ambitious Use Cases Built on Shaky Technical Foundations

Some of the initiative’s marquee use cases - “Kill the Clipboard,” conversational AI, and precision apps for diabetes or obesity - sound compelling. But the gap between concept and execution is vast.

Take “Kill the Clipboard.” It requires seamless FHIR-based exchange at check-in, standardized patient identities, and providers ready to ingest external visit summaries in real time. Most practices can’t even exchange CCDs reliably today - let alone coordinate across apps, QR codes, and federated APIs.

Similarly, AI assistants built on fragmented, incomplete patient records are not just unhelpful - they’re dangerous. Even the most advanced large language models struggle to reason over contradictory or missing data.

There’s nothing wrong with aspirational use cases. But presenting them as baseline expectations risks setting the initiative up for disappointment - and feeding skepticism that it’s all just another health IT moonshot.

7. The Chicken-and-Egg Problem of Network Adoption

The CMS ecosystem only works if everyone jumps in together. That’s a tall order in a sector where inertia is often the strongest force.

Networks won’t invest unless they’re confident providers and payers will participate. Providers won’t join if patients don’t demand it. Patients won’t use apps unless their doctors support them. And payers won’t share claims data unless forced by regulation or peer pressure.

CMS is hoping voluntary momentum will overcome this catch-22. But history tells us otherwise. Prior interoperability efforts - from HITECH to the 21st Century Cures Act - only moved the needle after mandates and incentives came into play. Betting on alignment without enforcement is, at best, a leap of faith.

8. Self-Attestation Isn't Real Accountability

The framework’s primary compliance mechanism is… self-attestation. Networks promise they meet the criteria. If someone complains, CMS might review. That’s about it.

There are no defined penalties for noncompliance. No audit schedule. No public dispute resolution process. CMS says it may develop scorecards and rely on user feedback to create transparency - but that’s a long way from meaningful accountability.

And without enforcement, bad actors can claim alignment, benefit from the branding, and continue business as usual behind the scenes. That’s not a minor loophole. It’s a structural flaw that could erode trust in the whole initiative.

9. Small Providers Lack Resources for Infrastructure Overhauls

For safety-net providers, rural clinics, and small practices, the idea of implementing these sweeping changes is borderline laughable.

Many still struggle with outdated EHRs, unreliable broadband, and skeleton IT teams. They’re already stretched thin trying to meet today’s requirements - adding voluntary infrastructure upgrades on top isn’t just unlikely, it’s infeasible.

And while the framework acknowledges this reality in tone, it doesn’t offer much in the way of material support. Without funding, technical assistance, or regulatory relief, these organizations may simply opt out - or be left behind.

Which means that the very communities this initiative hopes to serve better - rural seniors, low-income patients, those with complex care needs - may once again find themselves on the outside looking in.

AI Won't Fix the Politics of Health Data Sharing

If you read the CMS documents closely, you’ll notice a quiet assumption running through the framework: that modern tech - especially AI - will help us leapfrog decades of health IT dysfunction. And on some level, that’s not wrong.

The last five years have seen a stunning acceleration in what AI can do. From generating code to parsing messy documents, AI agents are already being used to solve problems that would’ve taken human teams weeks. In a vacuum, it’s entirely plausible that the right AI could build a FHIR API, convert HL7 messages, or map nonstandard lab codes to LOINC in a fraction of the time it would take a traditional dev team. There’s genuine potential here:

• Code scaffolding & FHIR implementation: AI can generate boilerplate interfaces, assist with data mapping, and even refactor legacy ETL pipelines.

• Terminology normalization: Pattern-matching across local vocabularies to standard coding schemes is exactly the kind of structured chaos AI handles well.

• Federated search optimization: AI agents could route queries across networks, reconcile incomplete responses, and present a coherent view to the end user.

But this is where the optimism runs into the system. Despite technical capability, most healthcare organizations won’t trust AI to touch core infrastructure - not when a single misconfigured query could compromise patient safety or violate HIPAA.

• Regulatory ambiguity: No one knows who certifies an AI-built FHIR pipeline. The FDA? ONC? CMS? That uncertainty makes legal and compliance teams deeply nervous.

• Human governance bottlenecks: You can’t LLM your way through a data-sharing agreement or shortcut a consent policy debate. The real delays live in conference rooms, not codebases.

• Institutional risk aversion: These same systems are still haunted by the ghost of IBM Watson Health. The bar for AI trustworthiness in healthcare isn’t “it works” - it’s “we won’t get sued.”

So while AI might solve technical hurdles, those aren’t the true bottlenecks anymore. The hard part is socio-organizational:

• Legacy contracts still limit interoperability.

• Business models still reward data hoarding.

• Training staff still takes time.

• Changing workflows still requires trust.

Which means that in this moment, AI isn’t the bulldozer. It’s more like the canary in the coal mine - drawing attention to the absurd friction we’ve come to accept. At its most transformative, AI’s role in this ecosystem may not lie in quiet back-end optimization - but in revealing the fractures in the system itself.

If a conversational agent can piece together a patient’s story across five disconnected portals in seconds, that doesn’t just solve a technical problem. It exposes a deeper one: Why can’t humans, or the systems we’ve built, do this already?

As patients interact with intelligent agents in other domains - assistants that remember preferences, respond fluidly, and anticipate needs - expectations around healthcare interfaces will shift. The more jarring the gap between what’s possible and what’s delivered, the more pressure there is on the system to change.

In practice, AI may function as shadow infrastructure - scraping PDFs, parsing emails, and reverse-engineering portals not because it's elegant, but because the official routes are too brittle, slow, or restricted. If these unofficial tools work better, even temporarily, they could compel the formal system to evolve. And in doing so, AI wouldn’t just assist the ecosystem — it would challenge it.

That may be the most honest contribution AI can make right now: not replacing clinicians or redesigning billing codes, but simply holding up a mirror.

What Success Would Actually Look Like-and Why It's Unlikely

The CMS Health Tech Ecosystem isn’t the first ambitious push to modernize health data. The 21st Century Cures Act promised to end information blocking. The HITECH Act poured billions into digitizing records. Each initiative moved the ball forward - but always with caveats, compromises, and uneven adoption. Having said that, this one feels different. Not because the technology is better (though it is), but because CMS is trying to harness the private sector’s momentum instead of dragging it along. It’s a bold bet: that voluntary coordination, open standards, and shared infrastructure will succeed where top-down mandates plateaued. And if it works - if CMS Aligned Networks become a real, functional ecosystem patients could finally experience something close to seamless care. That would mean:

• No more re-explaining your history every time you see a new doctor.

• No more wondering if your PCP ever got the specialist’s notes.

• No more black boxes where your data should be.

But here’s the hard truth - this is going to be messy. The incentives aren’t fully aligned. The governance structures aren’t fully built. And the initiative is launching into a system that resists change on its best day. What it needs - beyond tech and enthusiasm - is vigilance. Oversight. Real conversations about power, profit, and who benefits from the friction that currently defines health IT. Because I strongly believe that progress will never look like a clean rollout. It’ll look like whack-a-mole:

• A promising app that gets throttled by EHR restrictions.

• A network that claims alignment while quietly keeping data closed.

• A well-meaning AI assistant that gives bad advice based on stale records.

Each of these will be dismissed as an exception. But collectively, they’ll determine whether this initiative thrives or quietly dissolves into yet another half-remembered chapter in the long, strange history of U.S. health tech reform.

So yes - this could be the beginning of something transformative. But only if we stay clear-eyed about the gaps, honest about the tradeoffs, and willing to keep asking the uncomfortable questions.

Cover image generated using OpenAI’s DALL·E with the following prompt

Create a 1920×1080 header illustration in a clean, flat-vector style with subtle gradients and a professional tech vibe. On the left, show a simplified hospital building icon. On the right, depict a stylized cloud containing the logos or nameplates “Amazon,” “Google,” and “OpenAI.” In the center, have a friendly doctor and patient shaking hands, with glowing data pipelines (label one “FHIR API”) linking the hospital, patient, doctor, and cloud. Dot small robot assistants and user-icon nodes along the pipelines. Use a palette of blues, teals, and purples with accent glows to convey secure, real-time health data flow.