Imaging infrastructure needs to catch up with how healthcare operates

PARTNER CONTENT As enterprise imaging grows more complex, storage is quietly becoming one of the most consequential and overlooked pieces of healthcare infrastructure. AI workloads, modality changes, and long-term retention requirements are exposing the limits of traditional planning models. The stakes are clinical, operational, and financial.

Today's imaging environments demand more than just capacity. Study volumes are rising. AI requires fast, repeatable access to historical studies. And clinicians expect imaging data to be instantly available, no matter the modality or age of the study.

Yet storage strategies haven't kept pace.

Most infrastructure teams are still planning and budgeting like it's five or ten years ago. That means making long-term bets on capacity, tying costs to data growth, or bundling storage into PACS contracts that lock teams in as needs evolve.

The result is a growing disconnect between the demands of modern imaging and the assumptions built into the systems behind it.

The early signs are subtle. They often show up outside of IT: delays in clinical workflows, slow AI response times, and access issues disrupt how clinicians and analysts work. What begins as a performance issue can quickly ripple into clinical delays, frustrated users, and mounting internal pressure to fix problems that traditional models weren't built to solve.

The cost of an outdated model

Imaging is generating more data than ever. Yet reimbursement remains flat. Providers still get paid once per study, early in the care cycle, while storage needs and performance demands continue for years. That mismatch creates long-term cost pressure that traditional models weren't built to absorb.

Many teams still treat storage as a capacity problem. But in enterprise imaging, access speed, uptime, and workflow performance matter just as much. As modalities evolve and AI adoption increases, infrastructure that can't keep up puts more than just IT at risk.

And because the original assumptions no longer hold, teams across the organization are left dealing with the fallout:

• Procurement teams face unplanned refreshes and expansion costs they didn't forecast

• Clinicians lose time waiting for studies like 3D mammography or CT scans to load

• AI workloads underperform when infrastructure can't deliver consistent access to archived data

• Finance teams see storage costs continue to grow, even after imaging revenue has already been recognized

This isn't about isolated missteps. It's a structural misalignment between how imaging is delivered and how storage is planned.

Why traditional approaches make it worse

Legacy models aren't broken because the hardware has changed. They're broken because healthcare has. CapEx, cloud, and bundled storage each introduce challenges that get harder to manage as imaging grows.

• CapEx models require teams to predict storage needs years in advance, then lock in capacity and performance levels that may not align with actual clinical demand. These fixed investments often lead to underutilized infrastructure. Even worse, they can cause performance gaps that surface before the next refresh cycle.

• Cloud-based or OpEx storage often ties costs to data growth instead of patient volume. As modalities evolve and archives expand, organizations get hit with unpredictable charges: egress fees, tiering penalties, or API costs that are difficult to forecast across budgeting cycles.

• Bundled storage tied to PACS or VNA contracts can simplify procurement in the short term. But over time, this tight coupling limits flexibility, complicates platform migrations, reduces bargaining power, and slows down infrastructure decisions that should be independent of software refreshes.

Each of these models asks healthcare organizations to absorb all the risk: guess what they'll need, bet on what it will cost, and hope the infrastructure can keep up with clinical priorities along the way.

But imaging workflows aren't driven by capacity. They're driven by speed, access, and uptime.

And that disconnect is what leads to overbuying, reactive upgrades, and performance gaps that frontline teams feel first.

There's a purpose-built alternative

Evergreen//One™ for Medical Imaging isn't a tweak to an existing storage model. It's the first solution built specifically for enterprise imaging, designed from the ground up to match how healthcare actually operates.

No other offering combines predictable per-study pricing with guaranteed performance, always-on access, and the flexibility to evolve with your imaging environment. It's a category-first approach that finally breaks the tradeoffs between cost, control, and clinical performance.

With Evergreen//One for Medical Imaging, storage aligns with care delivery, not just data growth. That means:

• You pay once per study, for the full contract term, even if study sizes double

• Performance is guaranteed, with no tuning, tiering, or refresh planning required

• Storage scales automatically, so you're never overprovisioned or caught off guard

• Older studies stay instantly accessible, supporting AI and diagnostic workflows equally

• You stay in control, with flexible deployment options and no vendor lock-in

Plus, with Pure Storage®, security and resilience are built in. Evergreen//One for Medical Imaging includes ransomware recovery SLAs, immutable SafeMode™ snapshots, and always-on protection for sensitive imaging data. SafeMode creates locked copies of your data that can't be modified or deleted, even by compromised admin credentials, helping organizations recover quickly and confidently after an attack.

And unlike legacy models, the operational risk doesn't fall solely on your team. Pure Storage guarantees the performance, access, and protection of your imaging data for the full term of the contract. You get built-in safeguards and binding SLAs, not loose promises or variable tiers. That means less reactive planning, fewer fire drills, and more confidence across the teams that rely on your infrastructure every day.

This is more than a new storage option. It's a new model for how imaging infrastructure is planned, priced, and supported.

What to watch for, and what comes next

Infrastructure decisions made five years ago weren't wrong, but they weren't built for where imaging is today. If you're feeling boxed in by cost, access, or contract constraints, now's the time to evaluate whether your model is still keeping pace with clinical and operational priorities.

Download the executive briefing to explore five key questions you can use to engage stakeholders across IT, clinical strategy, imaging, and finance, and start a better conversation about what your infrastructure really needs next.

Download now →