Hospitals and imaging providers are under pressure to deliver more. Study volumes are rising. AI is driving new demands, and clinicians expect imaging to be instantly available, regardless of size, modality, or age.

Yet storage strategies haven’t kept pace.

Most infrastructure teams still plan and budget 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. Performance issues quickly ripple into clinical delays, frustrated users, and mounting 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The cost of an outdated model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 years in advance and lock in capacity that may not align with actual demand.
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 costs, hidden fees, or storage tiers that don’t deliver consistent performance.
Bundled storage tied to PACS or VNA contracts can simplify procurement in the short term, but over time, it limits flexibility, complicates vendor transitions, and makes infrastructure harder to evolve.

Each model pushes the risk onto providers: guess what they’ll need, bet on what it will cost, and hope the infrastructure can keep up with clinical priorities.

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 and 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

And unlike legacy models, the risk isn’t on you. Pure Storage® takes it on, guaranteeing performance, access, and predictability so you can focus on care, not capacity.

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 →

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