May/June 2026 Issue

Imaging Informatics: Connecting Silos
By Charles Morris
Radiology Today
Vol. 27 No. 3 P. 28

The Next Phase of Enterprise Imaging: Connected, Cloud, and Clinician-First

Radiology is entering a period of fundamental change. Imaging volumes continue to rise, clinical use cases extend far beyond traditional radiology departments, and health systems face persistent workforce shortages across both clinical and IT teams. Under these pressures, the limitations of traditional PACS are becoming increasingly apparent. As a result, imaging is being reexamined, not as a standalone system, but as a core component of enterprisewide digital infrastructure.

This shift has accelerated quickly. Until recently, most health systems focused their imaging strategies on replacing or upgrading PACS. Today, those conversations increasingly center on enterprise imaging, reflecting a broader recognition that imaging must support collaboration across specialties, streamline operations, and align with long-term digital transformation goals. Enterprise imaging is no longer a niche concept; it is becoming foundational.

At its core, enterprise imaging represents a move from isolated systems to a multimodality mindset. Rather than serving a single department, enterprise imaging brings acquisition, storage, viewing, reporting, and collaboration into a unified framework. This evolution mirrors the trajectory of EHRs, where fragmented tools eventually gave way to integrated platforms capable of supporting enterprise-scale workflows. As enterprise imaging solutions have matured and demonstrated their ability to meet clinical and operational demands, adoption has followed.

Unified Imaging
When imaging systems remain siloed, their limitations emerge at every level of the organization. Administratively, managing multiple best-of-breed systems creates significant complexity. Each system requires its own configuration, interfaces, upgrades, security controls, and disaster recovery planning. As these systems multiply, complexity grows, stretching limited IT resources and increasing the risk of gaps and inconsistencies.

These challenges are not purely technical. Many organizations have spent decades building customized imaging environments, with workflows and expertise shaped around maintaining fragmented systems. Moving beyond this model often requires a cultural shift as much as a technological one.

Clinically, silos undermine efficiency and confidence. When images, reports, and metadata reside in separate systems, keeping patient information current and synchronized becomes difficult. Updates may lag or fail to propagate altogether, leading to incomplete or outdated data in the patient record. Manual reconciliation remains common, adding hidden labor and increasing the potential for error.

Workforce shortages and cybersecurity threats further intensify the problem. As imaging demand grows—driven in part by an aging population—health systems have fewer staff to manage increasingly complex environments. At the same time, health care organizations face escalating cyber risks. Every additional system represents another access point that must be secured and monitored. Fragmentation multiplies both cost and exposure.

In contrast, a connected enterprise imaging environment is built on convergence rather than aggregation. Instead of wiring together multiple applications, a unified platform operates on a shared data model and technical infrastructure. This approach creates a single source of truth for imaging data, standardized metadata across specialties, and consistent access for clinicians—from radiology and cardiology to dermatology and surgery.

Equally important, connected environments support a unified viewing experience. Diagnostic interpretation, clinical review, referring physician access, and patient engagement can all draw from the same real-time data. Because the systems that generate imaging data are the same ones that display it, updates are immediate and consistent. For organizations accustomed to managing disconnected systems, this represents a fundamental shift toward simpler operations and more collaborative care.

Cloud as Catalyst
For many health systems, cloud adoption is driven less by technology trends than by operational necessity. Modernization is increasingly enabled by software-as-a-service (SaaS) delivery models that shift the burden of running complex imaging environments away from internal teams. As enterprise imaging platforms grow more capable, maintaining them on-premises requires specialized expertise and staffing levels that are increasingly difficult to sustain.

SaaS models offload system operation, maintenance, and lifecycle management, allowing health systems to redirect scarce resources toward clinical priorities. Imaging platforms across departments share many foundational functions: acquisition, storage, distribution, and visualization. Deploying these capabilities once and reusing them across the enterprise reduces redundant infrastructure and unnecessary labor.

Beyond staffing relief, SaaS simplifies operations. Instead of mastering system architecture, storage design, and upgrade cycles, internal teams can focus on clinical adoption and workflow optimization. The emphasis shifts from learning how to run the system to learning how to use it effectively.

Security is another major driver. As cyber threats escalate, centralized cloud environments allow patching, monitoring, and resilience planning to be handled consistently and proactively. Modern cloud architectures are designed to address latency, bandwidth, and availability concerns through optimized image delivery, private connectivity, and distributed system design. As a result, cloud-based imaging is increasingly viewed not as a risk but as a path to greater reliability.

Reducing Burnout
Radiologist burnout is driven by two interconnected forces: rising workload and the growing amount of nonclinical work required to complete that workload. Imaging volumes continue to increase while the radiology workforce struggles to keep pace, forcing longer hours and expanded coverage. In this environment, even small inefficiencies accumulate quickly.

Clinician-first system design starts with recognizing the reality that radiologists work until the work is done. The goal is not simply to read faster, but to complete a demanding day without unnecessary cognitive strain and still have time outside the reading room.

Decision overload is a major contributor to fatigue. Traditional worklists require constant choices about what to read next and how to prioritize cases. Intelligent workflow orchestration can reduce that burden by assigning studies dynamically based on urgency, rules, and available staffing. When work is distributed fairly and transparently, radiologists can focus on interpretation rather than logistics.

This aligns with the concept of “flow,” a state in which clinicians move through their day with minimal interruption, maintaining focus on patient care rather than technology. Flow does not eliminate complexity, but it minimizes friction. Systems that behave predictably and align with clinical training help distractions fade into the background.

Automation and augmented intelligence also play a role. In many cases, its greatest benefit lies in prioritization, quality assurance, and acting as a silent second reader. Over time, clinician-first intelligence will depend on delivering relevance rather than volume, surfacing the right information at the right moment without creating new distractions.

Digital Transformation Drivers
As imaging becomes embedded across the enterprise, modernization is no longer a departmental decision. Radiology leaders increasingly serve as digital change agents, bridging clinical priorities, IT strategy, and organizational governance.

Historically, radiology often led hospital IT initiatives because it managed large data volumes early on. Today, imaging is ubiquitous, and responsibility for imaging infrastructure typically resides within centralized IT organizations. Success now depends on partnership. Radiology leaders must collaborate closely with IT teams while contributing clinical insight and workflow expertise.

Enterprise imaging is also not a simple system replacement. The term is used broadly and can describe very different approaches. Organizations must look beyond labels and focus on desired outcomes—such as interoperability, scalability, and workflow improvement—rather than assuming enterprise imaging is a like-for-like PACS replacement. Conceptually, the shift is less like changing tires and more like changing vehicles entirely.

Over the next three to five years, enterprise imaging will continue evolving into a strategic clinical and operational platform. AI will mature across multiple dimensions, supporting interpretation, clinical coordination, and administrative oversight. Platforms—some already there—will continue to expand beyond radiology and cardiology into a wider range of imaging specialties, strengthening the concept of an imaging medical record.

Workflow orchestration will become more predictive, helping keep clinicians in flow and aligning work with patient urgency. The availability of cloud-based solutions, with a SaaS delivery model, will continue to accelerate, benefiting both health systems and independent radiology practices operating across distributed environments.

The key takeaway is clear: enterprise imaging is no longer about replacing systems. It is about rethinking how imaging supports care delivery as a whole. The next phase will be shaped by interoperability, cloud-enabled scalability, workflow-native intelligence, and human-centered design, creating imaging environments that are more connected, resilient, and sustainable for the people who depend on them every day.

— Charles Morris is the director of enterprise imaging strategy for North America at AGFA HealthCare.