The conversation around radiologist burnout usually focuses on the sheer volume of work. This pressure is well documented, but recent analysis suggests the reality is even starker than previously thought. A 2022 Radiology paper indicates that when accounting for standard interruptions, radiologists often have less than one second per cross-sectional image to meet current standards of care.

However, volume is only half the equation. Beyond the number of studies, friction plays a significant role in exhausting our workforce. During a session at a past RSNA conference, experts like Dr. Jay R. Parikh and Dr. Frank Lexa highlighted that workflow inefficiencies, the clicks, the logins, and the searching, are a primary driver of burnout.

While we cannot easily solve the global shortage of radiologists, we can solve the technical inefficiencies that make their days harder. This starts by distinguishing between the legacy methods radiology has relied on and the modern interoperability standards the rest of healthcare has already adopted.

The "Exchange" Trap

‍In the broader healthcare landscape, "Interoperability" refers to the seamless, coordinated use of data across different systems. However, radiology has historically settled for a much narrower definition: Image Exchange.

"Image Exchange" is purely transactional. It focuses on simply moving a file from Point A to Point B, often ending with a link to an external portal or a CD upload. While this technically moves the data, it fails to achieve true interoperability because it does not integrate that data into the clinical workflow.

When organizations settle for simple exchange, they inadvertently place the burden of integration on the user. The radiologist is forced to:

• Hunt for the file in external portals.
• Switch contexts and log into different systems.
• Mentally integrate the prior exam with the current one without side-by-side comparison tools.

This gap between "exchanging a file" and "interoperable data availability" creates a high degree of cognitive friction. It turns a clinical task into an administrative hurdle, draining the mental energy radiologists need for diagnosis.

Centralizing the Narrative

To close this gap, radiology must catch up to the rest of the healthcare ecosystem. In a presentation on optimizing efficiency, Drs. Stacy O’Connor and Dorothy Sippo emphasized "workstation optimization" as a key defense against burnout. They argue that the only way to protect the workforce is to take manual tasks out of human hands entirely.

Achieving this optimization requires utilizing the healthcare organization's main source of truth: The Electronic Health Record (EHR).

While radiologists naturally spend the majority of their clinical time within the PACS, the EHR remains the definitive system of record for patient context, orders, and longitudinal history. When the EHR serves as the central hub for availability, organizations achieve two critical goals:

• A Unified Patient Narrative: By ingesting external imaging data directly into the EHR workflow, providers have immediate, context-aware access to the complete patient narrative. This mirrors the interoperability they expect with labs and medications, eliminating the need to search for "missing pieces."
• Maximizing the Human Investment: Hospitals spend significant capital training their staff to be proficient in their EHR. Leveraging this existing familiarity is a people-first strategy. Keeping the workflow within the environment they already know respects their "muscle memory" and lowers cognitive load, sending a clear message that the organization is investing in their well-being.

Why AI Alone Hasn’t Reduced Radiologist Burnout

‍For years, the industry hoped AI would be the solution to this crisis. However, recent research indicates this promise has yet to materialize.

A 2026 review published in European Radiology by Dr. Parikh and Dr. Lexa challenges the assumption that AI is currently reducing burnout. Their analysis found that "the balance of data does not support that AI improves the drivers of burnout," describing the current impact of AI as a "black box." This finding aligns with what we observed in our recent post, RSNA 2025 Recap: Moving From "Pixel AI" to Operational Reality. Adding diagnostic "Pixel AI" tools to a broken workflow often creates more noise rather than less.

The issue isn’t AI capability. It is where AI is inserted into the workflow.

To actually alleviate burnout, the focus must shift to Operational AI, which automates administrative burdens like data ingestion, patient matching, and hanging protocols before the radiologist even opens the study. However, these automation engines need raw, ingested data to function; they cannot operate on a simple "Exchange" hyperlink. By prioritizing deep integration, organizations unlock the ability to automate the "grunt work" of radiology. This is the missing link that moves AI from a theoretical promise to a practical tool for reducing burnout.

Protecting the Workforce Starts With Fixing the Systems Around Them

‍Ultimately, the goal of technology should be to support the people behind the screen. As Dr. Parikh stated, the industry mindset must shift from "no margin, no mission" to "no people, no mission."

Investing in seamless data availability is a direct investment in the people who deliver care. We must stop asking healthcare workers to compensate for broken technology with their own time and mental health. Instead, we must provide tools that respect their time, preserve their focus, and support their well-being.

From Interoperability Strategy to Real Workflow Relief

‍If you are ready to move beyond simple exchange and start building a workflow that truly supports your clinical teams, there are practical steps you can take today.

• Go Deeper: Read more about how Operational AI is reshaping the industry in our recent RSNA recap.
• See It in Action: If this approach resonates with your organization’s goals, explore our SMART on FHIR Applications to see how deep integration works in practice, or book a consultation to discuss your strategy with an expert.