How Multi-Site Imaging Networks Balance Radiologist Workload Across Locations

Published research and workforce data show how multi-site imaging networks balance radiologist workload across locations as practices keep consolidating.

By Trisha Seal — October 1, 2026. Trisha writes about case intake, routing, scheduling, and workforce operations drawn from RAD365's work on the Radiology Workflow Manager. RAD365 does not read or interpret studies.

As radiology practices consolidate into larger, multi-site networks, "how much workload is reasonable" stops being a one-building question. Here is what published research and workforce data say about balancing it across locations.

Radiology practices have been consolidating for a decade, and the data shows it: the average number of radiologists per practice rose from 9.7 to 17.9 between 2014 and 2023, an 85% increase, according to the American College of Radiology's Harvey L. Neiman Health Policy Institute. As practices grow into true multi-site networks spanning several hospitals and imaging centers, a question that used to be simple, how much radiologist workload is reasonable, gets a lot harder to answer when the same group covers five locations instead of one.

Why Workload Imbalance Happens Across Sites

Different sites generate different case volumes, different modality mixes, and different acuity levels, even within the same network. A Level I trauma center and a suburban outpatient imaging center rarely produce comparable reading loads. When cases are assigned by site of origin rather than by actual radiologist capacity, some readers end up consistently busier than others, and that imbalance tends to compound as a network adds locations rather than resolve itself.

What Published Research Shows Is Possible

A 2023 study in the Journal of Digital Imaging described a RIS-integrated workload-balancing system built for a multi-hospital network in Reggio Emilia, Italy, covering a main hospital, Arcispedale S. Maria Nuova, and five smaller district hospitals. The system used a rules-based algorithm within the radiology information system that assigned incoming exams to whichever on-duty radiologist, across either of two teams, currently carried the lowest workload, while keeping all exams from a single patient episode with the same radiologist to preserve continuity of care.

The authors reported that the system successfully balanced radiological activity between teams of different radiologists across the network while preserving continuity of care and the radiologists' confidence in their own reporting. The published findings describe this as a successful qualitative implementation rather than a specific quantified percentage improvement, but the underlying principle, balance workload dynamically across sites while protecting continuity rules, is the one more networks are now trying to operationalize.

Workforce Pressure Is Raising the Stakes

The American College of Radiology's Harvey L. Neiman Health Policy Institute has reported that radiologists are leaving practice entirely at roughly twice the rate they were less than a decade ago. Subspecialty radiologists are 37% more likely to exit the workforce than generalists, and the number of pediatric radiologists specifically declined from 2,190 in 2016 to 2,032 in 2023, a drop from 6.4% to 4.6% of all radiologists over that period. That combination, fewer subspecialists and higher overall attrition, means a network cannot simply split volume evenly across available readers. Subspecialty cases still need to reach radiologists who can actually read them, even as that pool shrinks relative to overall demand, a pattern that also shows up in why radiologist productivity varies so much between departments.

Why Growing, Consolidated Networks Feel This Most

The consolidation data is specific: the number of distinct radiology practices fell 14.7% between 2014 and 2023 while the total number of radiologists grew 17.3%, meaning the same (or a growing) pool of radiologists is now concentrated in fewer, larger groups. Multispecialty practices grew 12% over that period while radiology-only practices declined 31%. Put together, radiology is consolidating into bigger, more geographically distributed networks, which is exactly the environment where ad hoc, site-based case assignment stops working and deliberate, network-wide workload balancing becomes necessary rather than optional.

What a Workflow Layer Needs to Do to Balance Load Across Sites

Based on the research above and the practical realities of a growing network, a workflow system built to balance radiologist workload across locations needs several things working together, the kind of consolidation RAD365's Radiology Workflow Manager is built around:

Consolidated intake: every referral source feeding into one queue rather than separate, site-specific worklists
Capacity-aware routing: cases routed by modality, body part, and subspecialty availability, not just by which site a study originated from
Availability-based scheduling: radiologists scheduled by actual availability, including across time zones where a network spans them, rather than a fixed roster that ignores real-time load
Continuous visibility: workload distribution tracked and reported on an ongoing basis so imbalance is visible before it drives a resignation, not discovered afterward
Continuity-of-care rules: the same logic the Reggio Emilia system used, keeping exams from a single episode with one radiologist even as the system balances new cases across the wider network

Ad Hoc Assignment vs. Structured Workload Balancing

Area	Ad hoc, site-based assignment	Structured, network-wide balancing
Case routing	By site of origin	By real-time radiologist capacity across the network
Subspecialty matching	Whoever is on the site's roster	Routed to available subspecialty-qualified readers network-wide
Continuity of care	Inconsistent across sites	Same-episode cases kept with one radiologist by rule
Visibility into imbalance	Discovered after complaints or attrition	Tracked continuously against workload data
Resilience to attrition	One site's gap stays a gap	Capacity elsewhere in the network can absorb it
Scalability to new sites	Each site added as its own silo	New sites plug into existing routing and scheduling logic

A Short Checklist Before Your Next Site Joins the Network

Map current case volume and modality mix at the new site before go-live
Identify any subspecialty coverage gaps the new site introduces
Define continuity-of-care rules for the new site's patients in advance
Decide what "workload" will be measured in: study count, RVU, or weighted complexity
Set up workload visibility and administrative reporting before imbalance becomes a problem, not after

RAD365 is an operations and workflow partner providing PACS Support and the Radiology Workflow Manager only. It does not read or interpret studies, and it does not provide preliminary reads, dictation, or reporting.

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Frequently Asked Questions

Why Workload Imbalance Happens

Why does radiologist workload vary so much across sites in the same network?

Different sites generate different case volumes, modality mixes, and acuity levels. A trauma center and a suburban outpatient center rarely produce comparable reading loads, so assigning cases strictly by site of origin tends to leave some radiologists consistently busier than others.

Is workload imbalance mostly a staffing problem or a routing problem?

Often both, but routing is usually the more fixable part. Adding staff addresses volume; it does not fix a system that keeps sending a disproportionate share of complex or high-volume cases to the same readers regardless of their current capacity.

Does case complexity matter as much as case count when measuring workload?

Yes. Two radiologists reading the same number of studies can carry very different actual workloads if one is reading mostly routine chest X-rays and the other is reading complex multi-phase CT studies, which is why networks increasingly weight workload rather than counting raw volume.

Can workload imbalance affect patient care, not just radiologist satisfaction?

It can. Consistently overloaded readers are at higher risk of fatigue-related errors and slower turnaround, while underutilized capacity elsewhere in the network goes unused, so imbalance is as much a quality and turnaround issue as a staffing one.

What Published Research Shows

Has anyone actually studied radiologist workload balancing across multiple hospitals?

Yes. A 2023 study in the Journal of Digital Imaging described a RIS-integrated workload-balancing system built for a multi-hospital network in Reggio Emilia, Italy, covering a main hospital and five smaller district hospitals.

How did that study's workload-balancing system actually work?

It used a rules-based algorithm within the radiology information system that assigned incoming exams to whichever on-duty radiologist, across either of two teams, currently carried the lowest workload, while keeping all exams from a single patient episode with the same radiologist.

Why did the researchers keep exams from the same episode with one radiologist?

To preserve continuity of care. Splitting a single patient episode across multiple readers can fragment clinical context, so the system balanced new cases across the network while protecting that continuity rule.

What did the study conclude about this approach?

The authors reported that the system successfully balanced radiological activity between teams of different radiologists across the network while preserving continuity of care and the radiologists' confidence in their own reporting, though the published findings describe this as a successful qualitative implementation rather than a specific quantified percentage improvement.

Workforce and Consolidation Pressure

Is the radiologist shortage making workload balancing more urgent?

Yes. The American College of Radiology's Harvey L. Neiman Health Policy Institute has reported that radiologists are leaving practice entirely at roughly twice the rate they were less than a decade ago, which puts more pressure on networks to use the radiologists they have efficiently.

Are subspecialists leaving the workforce at a different rate than generalists?

Yes. The same research found subspecialty radiologists are 37% more likely to exit the workforce than generalists, which matters for workload balancing because subspecialty cases cannot simply be routed to any available reader.

Is pediatric radiology specifically affected by this trend?

It appears to be. The number of pediatric radiologists declined from 2,190 in 2016 to 2,032 in 2023, and their share of all radiologists fell from 6.4% to 4.6% over the same period, according to ACR Bulletin reporting on HPI workforce data.

Why are radiology practices consolidating into larger, multi-site groups?

Practice data shows the average number of radiologists per practice rose from 9.7 to 17.9 between 2014 and 2023, an 85% increase, even as the total number of distinct practices fell 14.7%. Multispecialty practices grew while radiology-only practices declined, suggesting consolidation is a broader trend, not an isolated choice by a few groups.

Building Balanced Multi-Site Workflows

What does a workflow system need to do to balance radiologist workload across locations?

At minimum, it needs to consolidate case intake from every referral source into one queue, route cases by modality, body part, and subspecialty availability rather than by originating site, and track workload distribution continuously so imbalance is visible before it drives a resignation.

Should workload be measured by study count or something else?

Many networks weight workload by case complexity rather than counting studies, since a complex multi-phase CT and a routine radiograph place very different demands on a radiologist's time even though each counts as one study.

How does time-zone-based scheduling relate to workload balancing?

They work together. Scheduling radiologists across time zones expands when cases can be read, while workload balancing determines which radiologist within that available pool gets the next case, so a network needs both pieces to actually smooth out imbalance.

What should a network check before adding a new site to its workload-balancing system?

Current case volume and modality mix at the new site, any subspecialty coverage gaps it introduces, how continuity-of-care rules will apply to its patients, and whether reporting and visibility tools are in place before go-live rather than added after imbalance appears.