Connected Is No Longer Enough: Building the Intelligent Imaging Environment

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Physician consulting with a radiologist in front of a PACS workstation.

Introduction

For years, one of medical imaging’s biggest challenges was system connectivity.  Easily accessing images outside of radiology and figuring out the best methods to share images across locations continues to be a challenge.  

Connecting disparate PACS environments, early on, was also a challenge.  Today, vendors have different solutions to handle cross-system integrations yet connecting data and system interoperability remains a challenge.  

Enterprise Imaging solutions created a foundation for bringing previously isolated information together. Today, cloud technologies expands possibilities for accessibility, scalability, and resilience, while standards like DICOM, HL7, FHIR, and DICOMweb continue making interoperability easier across increasingly diverse environments.

But given the limitations that exist, the reality is healthcare has made tremendous progress in providing the tools that allow better collaboration and data (and image) sharing.  The result is that most imaging ecosystems are more connected than ever before, but even with better connectivity, we’ve created new challenges.

The question becomes…what happens next?

From Connection to Coordination

Connecting systems allows information to move, but it doesn’t determine what should happen when that information arrives.  Does it go to a specific person or a general location waiting to be assigned?  Does a process or action need to be initialized when the data arrives?  What happens if the person the data is intended for isn’t available?  These and many more workflow scenarios need to be resolved to ensure data is acted upon properly when it’s received.

Today’s imaging environments may include multiple PACS, archives, cloud services, AI applications, clinical systems, connected and disconnected external organizations, and increasingly complex workflows that span facilities and specialties.

Every new connection creates an opportunity, but it can also create another process that must be managed. With staffing challenges that continue to persist, how do we make sure human-in-the-loop workflows are not a bottleneck in complex patient care pathways?

Consider something as seemingly simple as moving an imaging study. Where should it go?  Does the destination change based on facility, modality, specialty, priority, or clinical context?  What about Artificial Intelligence (AI)?  Should an AI application be used as part of the workflow process and which algorithm is best suited for the clinical condition on the inbound study. Where does it go once the results are provided?

Will an inbound study trigger other workflows and what happens if a system in the workflow loop is unavailable?  If it’s appropriate for technology to provide the final decision, should a human still be involved in the loop to evaluate the outcomes?

These are just a few of the scenarios and questions that need to be asked when planning complex workflows and they are not connectivity questions.  These are questions of orchestration – and they are becoming increasingly important as medical imaging environments grow more complex.

When Visibility Changes What Is Possible

Coordination becomes even more powerful when organizations understand what’s happening across their imaging environments as well as what needs to happen when data arrives.

Medical imaging generates enormous amounts of operational information, yet much of that information remains buried within individual applications and workflows. That data may be difficult to access with some of today’s systems and could be important to the patient’s care.

Oftentimes, to drive organizational changes, leaders need greater visibility into what’s happening and what should be happening – and we’re not just talking about operational dashboards.  

Determining where bottlenecks are developing in a given workflow process and what adaptations or workarounds are routinely initiated to keep data flowing are often just as important as making sure the right data arrives to the right place at the right time.  Once you understand what is happening with your data, you can begin to see how those workarounds are potentially impeding, or slowing down, patient care.  

When it comes to imaging studies, you need to understand if they are moving as expected and getting to the right person at the right time?  If not, understanding the hold-ups can help you solve data delivery problems in the future without human intervention.  In any workflow system, figuring out what processes are requiring intervention are the ones you should focus on first.  Determine if you have the technology in place today to solve those challenges or if new technology is required, and/or updated processes are necessary to address these problem areas.

You may be surprised to find underutilized resources in your process but understanding those under utilizations can help you improve future workflows.  Established workflows that may have worked in the past can suddenly become cumbersome or broken with today’s new demands.  You may even find different workflows for the same process across different facilities, these differences can affect clinical operations.

Traditional system monitoring can certainly tell an organization whether an application is functioning at its peak performance, but operational intelligence looks at how the overall “environment” is performing and that distinction matters.

When healthcare organizations gain better visibility across all systems and workflows, they can begin moving from reactive management toward proactive operations.  Instead of simply responding to problems, they can now begin to identify patterns, understand root causes, and improve the broken processes behind them.

Insight Becomes More Valuable When it Drives Action

Visibility creates understanding, but understanding alone doesn’t change an outcome.

Knowing that studies are consistently being delayed, that a particular workflow requires unnecessary manual intervention, or that information isn’t reaching the right destination provides valuable insight. The greater opportunity comes when organizations can use that insight to improve what happens next.

Sometimes the appropriate response is automated.  Such as a study is dynamically redirected based on clinician availability, study priority, specific location, or clinical need. A workflow is initiated when a specific event occurs or information is delivered to another application for additional processing. An AI service may be invoked based off of specific information or a task might be automatically prioritized.

Other situations require people in the mix to intervene.  An operational issue may need to be surfaced to an administrator to act upon, or a clinical exception may require additional review. A workflow may reach a point where human judgment, not another automated rule, is the appropriate next step in the overall process.

Sometimes, the environment itself needs to adapt.  If a system becomes suddenly unavailable, workflows may need to be redirected. If imaging volumes suddenly increase, resources may need to be dynamically adjusted. If a new AI application or clinical partner enters the ecosystem, existing workflows may need to incorporate these new capabilities without creating another isolated process.

This is where operational intelligence and workflow orchestration begin working together.

Operational intelligence provides the visibility and context needed to understand what’s happening across the imaging environment. Workflow orchestration provides the ability to coordinate what happens next, across systems, applications, information, rules, and available people.  Together, they create something more powerful than either capability can provide alone.

Instead of an imaging environment that simply transports information between connected systems, organizations can begin creating an environment capable of observing conditions, understanding context, coordinating workflows, and enabling the appropriate response.  And most importantly, the goal isn’t automation for automation’s sake.

The goal is to remove unnecessary friction in the overall process while keeping people involved where their expertise, judgment, and clinical knowledge create the most value.  That’s the progression from connectivity toward intelligence:

Connect. Orchestrate. Understand. Act.

  • Connect the systems and information that make up the imaging enterprise.
  • Orchestrate how information, applications, workflows, and people work together.
  • Understand what’s happening across the environment and where opportunities or problems are emerging.
  • Act by automating the appropriate response or empowering people with the information they need to make better decisions.

Those four capabilities represent an important evolution in how we think about medical imaging. Connectivity made information available, where imaging intelligence is about making that connected environment more useful, responsive, and ultimately more valuable to the people who depend on it.

Preparing for an AI-Enabled Future

Artificial intelligence (AI) makes this evolution from connectivity to coordination even more important.  Healthcare organizations are evaluating an expanding ecosystem of AI applications designed to support detection, prioritization, workflow efficiency, clinical decision-making, and operational improvement.

But deploying another algorithm isn’t necessarily the difficult part.  Integrating that new AI algorithm meaningfully into existing clinical and operational workflows often is.  Proper analysis needs to occur to determine which studies should be analyzed by this new algorithm and creating the workflow process steps to ensure it happens automatically.  It’s just as important to determine if the AI algorithm should even be part of the workflow.

Once the algorithm is initiated on a clinical study, determining where the results should go and who is the best person available to review them must be incorporated into any workflow process.  Then, once the results have been analyzed, what should happen with that information?  Who needs to know and how will follow-up be tracked?

As more and more AI algorithms become available on the market and FDA approved, how should organizations choose, introduce and plan for these new solutions?  They need to be incorporated into the overall workflow process, but the challenge is ensuring they don’t create another collection of disconnected applications and one-off workflows.

An intelligent imaging environment shouldn’t require healthcare organizations to redesign their infrastructure every time a new technology emerges.  It should provide a foundation capable of incorporating innovation as needs change.  That’s why AI readiness isn’t simply about having access to AI, it’s about creating an environment capable of putting AI to work that truly will improve the overall workflow and clinical processes it was designed to provide.

Resilience is Part of Intelligence

There’s another dimension to intelligent imaging that sometimes gets overlooked: resilience.  Medical imaging has been and continues to be an increasingly mission-critical infrastructure in virtually every health system.

If information becomes unavailable because of an outage, cyberattack, network interruption, or system failure, the consequences can quickly extend beyond IT.  Clinical workflows slow down significantly, physicians lose access to important patient information, and patient care can ultimately suffer as well.

An intelligent imaging strategy therefore must consider not only how information moves during normal operations, but how the environment responds when normal operations are disrupted making data protection, redundancy, recovery, and the ability to intelligently redirect workflows when normal operations cease to exist, part of the larger architecture.

The goal isn’t one-sided – to keep data available. It’s to help imaging operations continue as close as possibto established workflow processes.

The Intelligent Imaging Environment

None of this means healthcare needs to abandon the infrastructure it has spent decades building, the reality is quite the opposite.

PACS continues to remain essential, as radiology operations continues to depend on it.  Enterprise archives are no less important, as all imaging studies must continue to be available via the EHR.  Cloud infrastructure remains essential to provide access to data from any location.  Clinical applications remain essential to provide insight into patient results as well as ensuring departmental operations can continue.

The foundation to this entire ecosystem upon which to build imaging intelligence?  Enterprise Imaging.  The opportunity now is connecting all those investments within an architecture capable of doing more with them.

An intelligent imaging environment brings together:

  • Connected imaging so information can move securely across the enterprise.
  • Workflow orchestration so systems, information, rules, and people can be coordinated.
  • Operational intelligence so organizations can understand how imaging is performing.
  • AI enablement so emerging technologies can become part of meaningful workflows.
  • Resilience so imaging operations can continue when disruption occurs.

And ultimately, action, turning information and insight into better operational and clinical decisions.  This is the progression from a connected imaging environment to intelligent operations.

The Next Chapter of Imaging

At InsiteOne, we’ve spent more than two decades helping healthcare organizations manage, protect, and connect medical imaging information.  But medical imaging is evolving, and so are we.  We believe the next evolution won’t be defined by another isolated application or another technology silo.  It will be defined by how effectively healthcare organizations can bring infrastructure, workflows, information, and intelligence together.

Over the coming weeks, we’ll begin sharing more about how we’re approaching the next chapter in medical imaging’s challenge, and what we’re building for the next generation of imaging.  We also can’t wait to share some new capabilities vitally important to this operational model, and share our thoughts and insights in Chicago at RSNA 2026.

We believe the future of imaging isn’t just connected.

It’s intelligent.

For more information on how InsiteOne can provide a tailored solution to meet your organization’s Imaging IT needs, including workflow orchestration and imaging intelligence solutions, contact us today at 866.467.4831 or visit us here.