Tag: PE

More Radiologists Working for PE Practices

Posted on by Brian Casey

The share of U.S. radiologists working for practices owned by private equity has skyrocketed over the past decade, from 1% in 2013 to 12% in 2023. That’s according to a new study in AJR that documents the growing trend of PE ownership in medical imaging. 

As we reported recently, the growing number of private equity acquisitions in healthcare has raised questions about PE’s impact on patient care.

  • In radiology, some industry observers worry that PE acquisitions are changing the specialty in fundamental ways, turning radiologists from owner-stakeholders into corporate employees.

The new study analyzed PE acquisitions from 2013 to 2023, with a specific focus on geographic variations. 

  • Researchers found 151 PE acquisitions of radiology practices in the U.S. over the 11-year study period, through December 2023. 

Key findings were broken down as follows…

  • The share of radiologists working for PE practices boomed (12% from 1%). 
  • PE-acquired practices were associated with 16% of all U.S. radiology locations.
  • The states with the highest shares of PE-employed radiologists were Nevada (47%), Arizona (44%), Alaska (29%), Texas (27%), and Florida (24%).
  • Companies accounting for the largest number of PE-employed radiologists were Radiology Partners (70%), LucidHealth (8%), and U.S. Radiology Specialists (7%).

The new findings echo previous research showing PE’s geographic penetration to be greatest in the West and Southeast. 

  • They also underline the extent to which Radiology Partners dominates PE acquisitions as it brings independent imaging practices under its umbrella. 

The Takeaway

The new study – along with other recent research – demonstrates the extent to which private equity acquisitions are changing the face of radiology. Researchers should take the next step and investigate PE’s impact on radiologists’ career satisfaction, and by extension, patient care. 

PE Practice Purchases Tick Up

Posted on by Brian Casey

Private equity acquisitions of radiology practices ticked up in 2024 after two years of declines. A new paper in JACR sheds light on PE purchases in radiology, which have raised concerns about the corporatization of medical imaging in the U.S.

Private-sector radiology historically consisted of independent imaging practices run largely by radiologist-owners who contracted with hospitals to read imaging exams.

  • That model has begun to break down as radiology attracts investment from private equity investors eager to roll up what they see as a fragmented industry into larger companies that can leverage market power.

But what’s good for PE investors may not be good for radiologists – or for healthcare. 

  • Private equity investment in healthcare providers has raised concerns that investors may be putting profits before patients.

The new study documents the rate of private equity investment in radiology from 2013 to 2024, based on queries of the Pitchbook and CB Insights databases, finding …

  • There were 113 PE-led radiology acquisitions over the full study period (out of a total of 4.3k radiology practices in the U.S. in 2023). 
  • PE radiology acquisitions peaked at 18 in 2021, fell for the next two years, and ticked back up to 10 in 2024.
  • Most of the radiology practices being acquired employed 50-99 radiologists.
  • PE-led acquisitions were most common in the South.

So what’s to make of the numbers? A total of 113 acquisitions over 10 years isn’t that many (although the authors caution that acquisitions of multi-state or national practices and imaging chains would be counted as a single deal). 

  • And the researchers acknowledge that there’s little data on the impact of corporatization on healthcare quality, at least in radiology (although they do cite a study showing that PE ownership was associated with an 8.2% increase in radiology prices).  

The Takeaway

Private equity investment in radiology practices may still be in the early stages relative to other medical specialties, but radiologists will watch PE acquisitions closely for signs of how the trend may impact them. The new study serves as an important baseline for tracking future activity.   

AI Detects Incidental PE

Posted on by Brian Casey

In one of the most famous quotes about radiology and artificial intelligence, Curtis Langlotz, MD, PhD, once said that AI will not replace radiologists, but radiologists with AI will replace those without it. A new study in AJR illustrates his point, showing that radiologists using a commercially available AI algorithm had higher rates of detecting incidental pulmonary embolism on CT scans. 

AI is being applied to many clinical use cases in radiology, but one of the more promising is for detecting and triaging emergent conditions that might have escaped the radiologist’s attention on initial interpretations.

  • Pulmonary embolism is one such condition. PE can be life-threatening and occurs in 1.3-2.6% of routine contrast-enhanced CT exams, but radiologist miss rates range from 10-75% depending on patient population.

AI can help by automatically analyzing CT scans and alerting radiologists to PEs when they can be treated quickly; the FDA has authorized several algorithms for this clinical use. 

  • In the new paper, researchers conducted a prospective real-world study of Aidoc’s BriefCase for iPE Triage at the University of Alabama at Birmingham. 

Researchers tracked rates of PE detection in 4.3k patients before and after AI implementation in 2021, finding … 

  • Radiologists saw their sensitivity for PE detection go up after AI implementation (80% vs. 96%) 
  • Specificity was unchanged (99.1% vs. 99.9%, p=0.58)
  • The PE incidence rate went up (1.4% vs. 1.6%)
  • There was no statistically significant difference in report turnaround time before and after AI (65 vs. 78 minutes, p=0.26)

The study echoes findings from 2023, when researchers from UT Southwestern also used the Aidoc algorithm for PE detection, in that case finding that AI cut times for report turnaround and patient waits. 

The Takeaway

While studies showing AI’s value to radiologists are commonplace, many of them are performed under controlled conditions that don’t translate to the real world. The current study is significant because it shows that with AI, radiologists can achieve near-perfect detection of a potentially life-threatening condition without a negative impact on workflow.

Viz.ai Adds PE Stratification

Posted on by Jake Fishman

Viz.ai announced the FDA clearance of its new RV/LV ratio algorithm, adding an important risk stratification feature to its pulmonary embolism AI module, while representing an interesting example of how triage AI solutions might evolve.

Triage + Stratification + Coordination – Viz PE becomes far more comprehensive with its new RV/LV integration, helping radiologists detect/prioritize PE cases and assess right heart strain (a major cause of PE mortality), while equipping PE response teams with more actionable information. 

  • This addition might also improve clinicians’ experience with Viz PE, noting the risk of developing AI “alert fatigue” when all severity levels are treated the same.

Viz.ai is So On-Trend – Signify Research recently forecast that AI leaders will increasingly expand into new clinical segments, enhance their current solutions, and leverage platform / marketplace strategies, as AI evolves from point solutions to comprehensive workflows. Those trends are certainly evident within Viz.ai’s recent PE strategy…

  • Viz PE’s late 2021 launch was a key step in Viz.ai’s expansion beyond neuro/stroke
  • Adding RV/LV risk stratification certainly enhances Viz PE’s detection capabilities
  • Viz PE was developed by Avicenna.AI, arguably making Viz.ai a platform vendor
  • Viz PE’s workflow now combines detection, assessment, and care coordination

The same could be said for Aidoc, which previously added Imbio’s RV/LV algorithm to its PE AI solution (and also supports incidental PE), although few other triage AI workflows are this advanced for PE or other clinical areas.

The Takeaway

Viz.ai’s PE and RV/LV integration is a great example of how detection-focused AI tools can evolve through risk/severity stratification and workflow integration — and it might prove to be a key step in Viz.ai’s expansion beyond stroke AI.

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