When Health and Human Services announced that the agency would crack down on “information blocking,” it sent a clear message: healthcare organizations will face real consequences if patient electronic health information access is compromised by faulty systems.
The intent is sound. Patients should have easy access to their health data, whether that means lab results, imaging, prescriptions, or physician notes.
But here’s the problem: much of what regulators classify as “information blocking” isn’t malicious at all. It’s the result of outdated systems, poor interoperability, and fragmented data infrastructure that make sharing information slow, difficult, or impossible. Unless the industry tackles these underlying issues, stricter enforcement won’t fix the problem. In fact, it could make it worse by exposing the gaps many organizations aren’t yet equipped to close.
The real problem
It’s easy to picture information blocking as a deliberate attempt to generate more fees or to keep patients tied to one provider. Although those cases do exist, far more often the barriers are technical. Many hospitals and health systems still rely on outdated electronic health record platforms that were never built to share information easily.
Even when newer systems are in place, interoperability is limited, with platforms using different standards and formats that make it difficult to move information across settings of care. Data is often scattered in silos – lab systems, imaging archives, pharmacy records, and physician notes that don’t connect – leaving patients with only fragments of their medical history. These gaps not only frustrate patients but also slow down clinicians, stall innovation, and create compliance risks.
The effect is the same as intentional blocking: patients are left waiting for lab results, scrambling to piece together prescriptions, or unable to share critical information with a new provider. As enforcement ramps up, healthcare organizations can no longer rely on workarounds or manual processes to fill the gaps. They need a plan to address the root causes of the problem, and that means modernizing the way data is managed and shared.
Why this matters now
The urgency around health data access is rising. New rules on interoperability and tougher enforcement mean organizations can no longer treat compliance as a box-checking exercise. Regulators expect proof that patients can get their records when they need them. Those that can’t risk fines, reputational damage, and closer scrutiny.
At the same time, outdated infrastructure creates ripple effects that go far beyond patient frustration. When records are scattered or incomplete, clinicians are forced to work without the full picture, slowing diagnoses and treatment decisions.
The problem also hampers innovation. AI should be making it easier to manage and share information, yet legacy systems and siloed data are delaying adoption. That means tools with the potential to improve outcomes and reduce costs are left underused.
In short, antiquated systems are now a liability on multiple fronts: regulatory, operational, and technological. Addressing those weaknesses isn’t just about avoiding penalties – it’s about making healthcare work better.
The path forward
Many healthcare leaders hesitate to tackle modernization because they see it as prohibitively expensive, disruptive, or complex. What often gets overlooked is that the biggest obstacles aren’t usually the price tag or the size of the project, but the idea that modernization requires replacing entire systems all at once. In reality, the most effective strategy is incremental and goal-driven rather than a massive replacement project.
A strong first step is to build a reliable data foundation with clear governance, metadata, and lineage. Without a full understanding of what data exists, where it resides, and how it moves across systems, sharing it consistently is nearly impossible. Investing in governance and metadata management gives leaders the visibility and confidence to ensure quality, privacy, and compliance.
From there, organizations can enable real-time access by using tools that track and share updates the moment they occur. Instead of waiting for overnight batches or manual uploads, these tools turn existing databases into live data sources without requiring a full system overhaul. That means lab results, medication lists, or discharge summaries can flow directly into patient portals and apps as soon as they’re available. Both patients and clinicians benefit from immediate access to the latest information.
Another important step is creating reusable building blocks by organizing data so it can be easily shared and adapted for different purposes. Instead of treating data as an accidental byproduct of daily operations, organizations can treat it as a resource designed to support reporting, analytics, clinical workflows, and even AI. This means setting up ways to pull information from different systems without having to move or duplicate it each time, making it easier to manage securely and put to work wherever it’s needed.
Together, these steps form the foundation of an “active data architecture” – one that is dynamic, self-organizing, and able to adapt as patient needs and regulatory requirements evolve. With this approach, both providers and patients know where the data is and how to find it.
The bottom line
Information blocking is a real problem, but enforcement alone won’t solve it. If healthcare organizations focus only on compliance, they’ll miss the bigger opportunity: building modern data foundations that not only meet regulatory requirements but also improve care delivery, empower patients, and enable AI innovation.
By taking a practical, incremental approach to modernization, healthcare leaders can ensure that when patients ask for their health information, the answer is no longer, “We’ll get back to you.” Instead, it’s, “Here you go.”
