I Don't Think Small Hospitals Should Have to Settle
Here's a controversial take: a lot of the talk about "healthcare equity" focuses on patients. But I'd argue the real battleground is on the provider side. Small hospitals, rural clinics, and independent diagnostic centers are being systematically underserved by the medical imaging industry. They're offered older generation equipment, stripped-down software packages, and worse service contracts—all while being asked to deliver the same quality of care as a major academic center. That's not just unfair. It's bad medicine.
Look, I've been reviewing quality and compliance specifications for medical equipment for over 4 years. In our Q1 2024 audit, we reviewed contracts for imaging equipment across 30+ facilities. The disparity between what a 200-bed community hospital gets quoted versus a 1,000-bed university hospital is... well, let's just say it's not a simple matter of volume discounts. I'm a quality inspector, not a pricing strategist, but I know a structural problem when I see one.
The Data Says One Thing. My Gut Says Something Else.
The numbers said that from a pure unit-cost perspective, offering a lower-tier CT scanner to a small hospital makes sense. Lower acquisition cost, lower service cost, and the volumes don't justify the premium machine. My gut said something was off. I couldn't shake the feeling that we were building a two-tiered system of care, and justifying it with spreadsheets.
Here's what my gut detected: the diagnostic accuracy gap isn't just about the tech specs on paper. It's about workflow integration, software upgrade paths, and the ability to handle complex cases. A small hospital that buys a five-year-old scanner design today is five years behind on algorithm improvements—that impacts real patients. I went with my gut on this one. Not every spreadsheet decision is the right one.
The Most Frustrating Part of This Situation
The most frustrating part of vendor selection for smaller providers: the assumption that "good enough" is acceptable. You'd think that in 2025, with advances in AI-assisted imaging and low-dose protocols, everyone would have access to the same core technology. But the reality is that many manufacturers segment their product lines so aggressively that a "small hospital" package is deliberately hobbled.
After the third time I reviewed a contract where a community hospital was quoted a machine that couldn't run the latest cardiac stent planning software—a feature that costs almost nothing to enable—I was ready to write a strongly worded memo. What finally helped was a shift in how we frame the question: not "what can they afford?" but "what do their patients deserve?"
The Mammography Example That Changed My Mind
I ran a blind comparison test with our clinical team: same mammography images from two different system generations. One was a current-generation system with advanced AI for density assessment. The other was a three-year-old system without it. 78% of the radiologists identified the older system's images as "less confident" in their reads—without being told which was which. The cost difference between the two systems? About $15,000 on a $300,000 purchase. On a system that will perform 5,000+ exams over its life, that's $3 per patient for measurably better diagnostic confidence.
That's the kind of calculation that spreadsheets miss. The upfront savings look good on a budget sheet. The downstream cost of missed or equivocal findings? That gets buried in a different department's ledger.
What This Means for Medical Imaging Today
Medical imaging is the backbone of modern diagnosis—from mammography for breast cancer screening to cardiac stent planning for coronary artery disease. If the imaging equipment in a community hospital is a generation behind, the patients there are getting a generation-behind diagnosis. That's not hypothetical. That's physics. The spatial resolution, contrast-to-noise ratio, and software capabilities of the scanner determine what can be seen and how accurately it can be characterized.
I get why some manufacturers do it. Segmenting the market is profitable. It allows them to sell older designs at a margin that would be impossible on a newer platform. To be fair, the purchasing constraints for small hospitals are real—capital budgets are tight, and the ROI case for a premium machine is harder to make when volumes are lower. But here's the thing: the solution isn't to sell them worse technology. It's to make better technology affordable.
A Note on Regulatory Context
We should also talk about the regulatory environment. The Philips Healthcare consent decree between 2021 and 2024 highlighted how seriously the FDA takes quality in medical devices. That consent decree was a painful lesson for the industry about the consequences of cutting corners. It reinforced something I've believed for years: quality isn't a negotiable feature. It's a baseline requirement.
The same principle applies to market segmentation. If a device is safe and effective for a patient in a large hospital, it should be safe and effective for a patient in a rural clinic. There's no regulatory exemption for "good enough for small hospitals." Holding smaller providers to a lower standard of technology is, in effect, creating a lower standard of care—even if everyone's paperwork is technically compliant.
What Should Change? Three Things.
- Feature gating needs to end. Software features that improve diagnostic accuracy should not be reserved for premium packages. AI-assisted reading, low-dose protocols, and advanced post-processing are not optional luxuries—they're standard tools that every radiologist should have.
- Service agreements should be equitable. Response times and parts availability shouldn't be slower because a hospital is in a rural area. The cost of a delayed diagnosis because a service engineer is three days out is measured in patient outcomes, not money.
- Pricing models should reflect total value. A lower purchase price doesn't mean lower total cost if the machine has lower throughput, higher maintenance costs, or lower diagnostic confidence. The conversation needs to move from "what's the sticker price" to "what's the value over the device's lifetime."
Responding to the Obvious Objections
I know what some people will say: "Small hospitals have smaller budgets. You can't expect them to pay for a Ferrari when they need a reliable sedan." I get that. Budgets are real, and I'm not suggesting every clinic needs a top-of-the-line research scanner.
But here's where I push back: the gap between a "Ferrari" and a "sedan" in medical imaging is much narrower than the industry pretends. The marginal cost of including current-generation software on a scanner that's already in production is minimal. The real reason for feature segmentation is market control, not cost. And that's a choice—one that prioritizes quarterly earnings over clinical equity.
Another objection: "If small hospitals can't afford premium equipment, that's a reimbursement problem, not a manufacturer problem." Partially true. But manufacturers have choices about how they respond to that reality. They can double down on segmentation, or they can innovate in ways that bring essential capabilities down the cost curve. The companies that choose the latter will find that today's small customer is tomorrow's loyal partner.
The Bottom Line: Small Doesn't Mean Less Important
When I was starting out in this industry, the vendors who treated my $5,000 consumable orders seriously are the ones I still recommend for $500,000 capital purchases. Small doesn't mean unimportant—it means potential.
The same logic applies at the health system level. A 100-bed hospital in a rural community is not a less important source of care than a 1,000-bed academic center. The patients there have the same right to accurate mammography readings, the same right to precise cardiac stent planning. The technology that enables those outcomes should not be a privilege of geography or budget.
I'm not saying every hospital needs the most expensive MRI on the market. I am saying that the floor for what's acceptable in medical imaging should be higher than it is. And that manufacturers—including us—have a responsibility to raise that floor, not just chase the ceiling.
That's my view. Probably not the most popular one in a quarterly earnings call. But I've seen too many quality reports that show a clear correlation between equipment tier and diagnostic outcomes. We can fix this. We just need to decide that it matters.
