Connected data will rescue healthcare

Right now, too many physicians and patients are trapped in a fragmented system. Information exists—but rarely in a form that’s usable or easily actionable. Too often, lab results arrive as scanned images. Medication histories show up late or unreadable. Critical details hide in pages no one has time to sift through.

What clinicians feel in those moments is not just inconvenience—it’s strain. They’re carrying the weight of navigating a complexity that shouldn’t sit on their shoulders in the first place. Many expect artificial intelligence (AI) to solve the problem but while it can be an important part of the solution, AI is only as smart as the data it feeds on and only as effective as the structure that enables it. When information is incomplete, inconsistent, or locked in silos, even the most advanced tools struggle to deliver meaningful insight.

AI plays an important role—but not by fixing fragmented data on its own. The work of organizing, connecting, and interpreting healthcare information still belongs to people and the systems they build. Where AI helps is after that foundation is in place: by bringing the right information forward at the right time, reducing the effort it takes to find what matters, and supporting better decisions in the moment of care. The next era of healthcare innovation won’t be driven by larger AI models. It will be driven by how well we prepare the information they rely on.

The benefits of AI

AI is already helping clinicians reclaim time. It drafts documentation, supports communication, and reduces administrative burden reducing the pressures that drive burnout.

A nationwide survey of more than 500 physicians and administrators conducted by athenaInstitute for its AI on the Frontlines of Care report found that 64% of clinicians said documentation-related AI reduces their workload, and nearly half identified “time saved” as AI’s most important benefit. What stands out is how often clinicians describe these savings in terms of what they get back: the ability to be present with their patients.

Less administrative pressure doesn’t just lighten their workload—it changes how they show up in the exam room. That’s powerful.

But these gains reveal a deeper truth: AI performs best when the information around it is complete, consistent, and interpretable. For too many medical practices across the nation, that’s the exception, not the rule.

AI only works when the data works

Clinicians consistently report difficulty accessing what they need when they need it, according to athenaInstitute’s research. Nearly half say they encounter inconsistent formats or information that is simply hard to locate. Only 2% report having timely, comprehensive visibility across systems.

This disconnect has real consequences. AI cannot flag early signs that a patient’s condition is worsening if key information is missing. It can’t prevent duplicative testing when records don’t follow patients across medical settings. It can’t strengthen clinical reasoning when the underlying information contradicts itself.

AI is a force multiplier, but it can only magnify what already exists. If the data is fragmented, the insight will be fragmented too.

This is why interoperability matters to every one of us, whether we realize it or not. For clinicians, it’s the difference between piecing together bits of information or having a clear picture of their patients. For patients, it’s the difference between reciting the same information repeatedly or speaking face-to-face with your physician, with no distractions.

AI adoption grows when it reduces friction in the workflows clinicians struggle with most: documentation, intake, communication, scheduling, and claims. Trust grows when AI is transparent, monitored, and clinically grounded. Safety grows when interoperability and standardization serve as the backbone of clarity.

Four shifts that will shape the future

The organizations that unlock AI’s full value will be the ones that build the strongest data foundation. Leading organizations will take four actions.

1. Curate, not accumulate. Clinicians don’t need more data. They need meaningful data that supports their ability to treat patients.

2. Standardize to simplify. Predictable structure in the data—formats, fields and definitions—reduces friction and cognitive load.

3. Make intelligence portable. Patients move. Their information should move with them—intact, interpretable, and ready to support the next moment of care.

4. Support intuitive interpretation. The best AI surfaces what matters, explains why, and reinforces—not replaces—clinician judgment.

When these elements come together, AI stops functioning as a series of disconnected tools and starts acting as a true intelligence partner—one that provides clarity instead of noise.

Healthcare has never lacked dedication, intelligence, or compassion. What it has lacked is clarity—the ability to see the full picture when it matters most. AI can help deliver that clarity, but only when it’s built on a system that speaks a common language. If we invest in connected, usable data today, we won’t just make healthcare more efficient. We’ll make it more human. And that’s the kind of progress and innovation patients, clinicians, and communities deserve.

Stacy Simpson is chief marketing officer at athenahealth and co-chair of athenaInstitute.