Today, we’re speaking with Faisal Zain, a distinguished expert in medical technology whose work has been pivotal in advancing the manufacturing of innovative diagnostic and treatment devices. With a deep understanding of the intricate web of healthcare data, he brings a unique perspective on the challenges and opportunities of making our health systems truly communicate with one another.
Our conversation will explore the different layers of healthcare data exchange, moving beyond basic connectivity to uncover what it truly means for systems to speak the same language. We’ll delve into the real-world consequences of data misinterpretation, the strategic imperative for new health tech companies to build for meaningful integration from the start, and how federal regulations are accelerating the entire industry toward a more unified and intelligent future.
Many health systems still rely on foundational tools like faxes, which only ensure data delivery. How does this differ from semantic interoperability, and what specific clinical or administrative burdens does this older approach create for providers? Please share an example of the contrast.
That’s a fantastic place to start because it gets to the heart of the problem. Foundational interoperability, the kind you get with a fax machine, is like mailing a letter. You can prove it was delivered to the right address, but you have absolutely no guarantee that the person who opens it can read the language it’s written in. It simply gets the data from point A to B. The burden this creates is immense. Imagine a nurse on an already overloaded ward receiving a faxed discharge summary. That piece of paper doesn’t magically populate the patient’s electronic chart. That nurse now has to stop, manually interpret the handwriting or blurry text, and painstakingly type that information into the right fields. This isn’t just inefficient; it’s a breeding ground for errors and a major contributor to clinician burnout. It checks a box for “data exchange,” but it does nothing to help with timely, automated clinical decision-making.
Even with structural standards, a diagnosis might be recorded as “heart attack” in one system and “myocardial infarction” in another. What are the real-world consequences of this inconsistency for patient care, and what costly workarounds do tech companies typically build to bridge this gap?
This is the next frustrating step up the ladder—structural interoperability. We’ve agreed on the format, maybe an HL7 message, which is like agreeing to speak English. But one system uses the slang “heart attack,” and another uses the formal term “myocardial infarction.” A human might understand they’re the same, but a computer often won’t. The real-world consequence for a patient can be severe. Their record might appear incomplete, leading to duplicate tests, or worse, a critical piece of their history could be missed, impacting treatment decisions. To cope, tech companies are forced into a constant, expensive cycle of building custom integrations and data-mapping middleware. They’re essentially creating translator bots for every single dialect. These solutions are brittle, time-consuming to build, and don’t scale. Every new client requires a new, custom-built bridge, which is a massive drain on resources.
Semantic interoperability leverages codes like SNOMED and LOINC via APIs like FHIR. Could you walk us through a step-by-step example of how using a standardized code for a diagnosis can automatically trigger clinical decision support and streamline discharge planning, eliminating manual tasks?
Absolutely. This is where the magic happens. Let’s take that heart attack example. In a semantically interoperable world, the physician doesn’t just type free text; they select the standardized diagnosis code ICD-10 I21.9 for “Acute Myocardial Infarction.” The moment that code is entered, the system understands its precise meaning. Instantly, a cascade of automated events can occur with no human intervention. The system can trigger a clinical decision support alert, reminding the care team of best-practice medications for post-infarction care. Simultaneously, it can automatically add the patient to a discharge planning workflow, flagging them for cardiac rehabilitation resources and scheduling necessary follow-up appointments. It’s the difference between a system that is a passive data repository and one that is an active, intelligent partner in care.
For a new health tech company, building for semantic interoperability from day one can seem daunting. What is the long-term strategic advantage of this approach over using quicker, custom integrations, and how does it directly impact a company’s ability to scale its operations?
It can definitely seem like the harder path initially, but it is unequivocally a strategic differentiator. Relying on quick, custom integrations is like building your company on a foundation of sand. Those solutions are brittle and require constant maintenance. Building for semantic interoperability is about creating a product that speaks the universal language of healthcare from its core. The long-term advantage is massive. It allows your solution to seamlessly plug into any health system that also speaks that language, which dramatically reduces implementation time and cost. For a company’s ability to scale, this is everything. You can’t grow exponentially if every new customer requires a six-month custom engineering project. By embracing standards like FHIR, you build once and connect everywhere, enabling richer analytics, reducing provider workflow friction, and ultimately delivering a far more powerful and valuable product.
Federal initiatives like TEFCA and the CMS Interoperability Rule are pushing for standardized data exchange. How do these regulations specifically accelerate the adoption of semantic interoperability for payers and providers, and what should entrepreneurs be preparing for as these frameworks become the norm?
These federal initiatives are the tailwind that the industry has desperately needed. Regulations like TEFCA and the CMS Interoperability Rule are essentially setting the rules of the road for the entire ecosystem. They are mandating the use of standardized, machine-readable data, moving beyond just encouraging it. For payers and providers, this is shifting semantic interoperability from a “nice-to-have” to a “must-do” for compliance and reimbursement. For entrepreneurs, this is a clear signal. The future is standardized. Instead of viewing this as a regulatory burden, they should see it as a blueprint for success. They need to be preparing by aligning their product architecture with these frameworks, like the USCDI v4 data elements, from the very beginning. Doing so ensures their solution will be relevant and easily adopted as the entire market moves in this direction.
What is your forecast for semantic interoperability?
My forecast is that we are at a tipping point. For years, true semantic interoperability has been the “holy grail”—something we’ve strived for but that remained just out of reach. Now, with the combination of maturing standards like FHIR, clear federal mandates, and intense market pressure to reduce costs and improve outcomes, we’re going to see a rapid acceleration. Foundational and structural workarounds will increasingly be seen as unacceptable liabilities. In the next few years, I believe semantic interoperability will shift from a competitive advantage to a baseline expectation. Companies that fail to build this into their core DNA won’t just struggle to scale; they’ll risk becoming obsolete as they’re left unable to communicate in an ecosystem that is finally beginning to speak the same language.
