Most health systems have put real money into diagnostic imaging, and in radiology it shows. Reads are faster, image quality is better, and the reading tools do what they were bought to do. Yet a cardiologist can still spend part of a morning tracking down a prior chest CT from another department, and an ED physician can still leave the EHR to look for outside imaging. Neither one means the PACS failed. They point to a different problem, one that sits between systems rather than inside any one of them.
A diagnostic PACS is built to make interpretation better, and a good one does exactly that. Enterprise imaging asks a different question: can any authorized clinician, in any department or facility, get to the imaging they need without a phone call?
Across most health systems, imaging still sits in disconnected systems, divided by department, facility or specialty. Each acquired hospital brings another PACS that works well locally and adds one more island to the enterprise. And imaging keeps spreading beyond radiology, into cardiology, pathology, ophthalmology and clinical research, each with its own systems and habits.
None of that is a sign that individual systems are weak. It is the natural result of how imaging environments grow. The issue is not whether each system works. It is whether they work together, and that takes something underneath them.
The idea at the center is simple to state. Separate imaging data and workflow management from the applications that use them.
When imaging data is tied to the system that created or manages it, every change to that system becomes a data problem. When the data is governed independently of any single system, the systems on top can be added, modernized or consolidated while the foundation underneath stays stable. Systems that already perform well keep doing their job. A shared foundation governs how images are stored, routed and accessed across the organization.
Workflow needs the same treatment. In most environments, workflow lives inside individual systems, so it stops where they stop. An enterprise layer manages how studies move across systems, departments and care settings. At Mach7 that layer includes rules-based routing with scheduled queries, HL7 order and result integration with clinical systems, and a vendor-neutral store with no proprietary internal format.
This is coexistence by design, not a compromise. Nothing that works has to be ripped out to get there.
The whitepaper walks through eight scenarios. Here are four that come up in almost every conversation.
Several PACS after a merger. A health system acquires three community hospitals, each running a different PACS. Clinicians at each site cannot easily see imaging from the others, and replacing all three at once is neither practical nor affordable. A foundation consolidates imaging data at the enterprise level and normalizes workflow across facilities, so the sites work in a coordinated way without any of them abandoning its existing system.
Priors stuck at a sister site. A patient arrives at one facility for urgent care, and the relevant prior imaging was taken at another. Without a shared data layer, moving that study depends on physical media or point-to-point connections, and the images may not arrive in time to inform the decision. A common foundation for data and workflow makes imaging acquired at any facility available to any authorized clinician, without every site running the same system.
Imaging outside the EHR. Clinicians increasingly expect to see imaging from where they already work. Imaging that is consolidated and indexed once is far easier to surface there than imaging scattered across departmental systems, and that is the part a foundation addresses. The integration itself is worth pinning down rather than assuming. Ask which EHR integration method a vendor supports, whether it is covered by a published conformance or integration statement, and what the clinician's workflow actually looks like. Mach7 publishes its conformance and integration statements openly, without a login, for exactly this reason.
AI that stays at one site. Imaging AI is often deployed at the point of reading, tied to one system or modality, with one tool at one facility and a different tool at another. An enterprise foundation is the right place to solve that. Mach7 can route a study to an AI algorithm, take the result back and act on it inside enterprise workflow. Mach7 does not read images or make clinical decisions: the algorithm produces its result and the clinician makes the decision. Set your routing requirements before you choose the algorithm, so adopting a new tool is a configuration decision rather than a rebuild.
The other four scenarios in the paper cover PACS modernization that stops at radiology, viewer access without the governance beneath it, downtime, and phased cloud migration on a vendor-neutral data layer.
A diagnostic PACS is strong at image interpretation, radiology workflow, departmental image management and high-performance reading tools. Keep it doing those things.
A foundation adds what sits across the enterprise: access across departments and sites, data governance and ownership, workflow orchestration between systems, imaging consolidated once and available to clinical systems, and a data layer that lets cloud moves happen in phases. The two play different roles, and an imaging strategy needs both.
You do not need a formal assessment to see where your gaps are. Put these questions to your own environment and to any vendor you are evaluating:
If the answers depend on one system being up, or on one vendor's roadmap, the gap is in the foundation, not the PACS.
Our whitepaper, Imaging Without Boundaries, walks through all eight scenarios, from multi-PACS mergers to phased cloud migration, with a practical way to approach each one. Download the whitepaper
Mach7 Technologies builds vendor-neutral enterprise imaging: the Vendor Neutral Archive, the Communication Workflow Engine, the eUnity enterprise viewer, AI enablement, and Flamingo, the next Mach7 product set.