Leadership

This news channel page highlights examples of leadership in hospital and health systems. While healthcare leadership is often seen as the positions of chief executive officers, chief clinical officers, chief of staff, and chief information officers, it also can can be other individuals or the entire healthcare system that shows unique ways to enhance patient care and manage strategies, quality, safety and revenue initiatives.

Distance learning’s 4 pros, 5 cons in radiology education

Challenged by the COVID pandemic to “match pedagogy with purpose,” many radiology educators have tapped technology to help keep residents from falling behind.

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Israel’s famously innovative healthcare system struggles to secure imaging devices

In some cases hospital staff kept no watch over outside-looking-in connections between manufacturers and scanners.

Unclear ownership, uneven assessments hamper informed-consent efforts in IR

The interventional radiology practice of an academic medical center has identified four challenges to securing informed consent from patients or their medical decision-makers. 

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3 indications auguring well for the future of pediatric PET/MRI

In pediatric care settings, hybrid PET/MR imaging combines “exquisite soft-tissue information obtained by MR imaging with functional information provided by PET.”

Portable MRI detects sports injuries near the point of play

Applied physicists have developed a portable MRI system that can screen young tennis players for wrist injuries in a minivan or suchlike passenger vehicle. 

Cross-sectional imaging ordered downstream for just 15% of emergency POCUS patients

Using point-of-care ultrasound in emergency settings does not lead to overutilization of follow-up imaging with cross-sectional CT, MRI or additional ultrasounds. 

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10 notable regulatory approvals of diagnostic devices over the past 30 days

Along with radiology-specific software and products, the list may include newly greenlit offerings for use in other settings that are increasingly important to multidisciplinary care.

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Most imaging AI algorithms perform unimpressively in external validation exercises

Some 81% of the models—70 of 86 DL algorithms reported in 83 separate studies—diminished at least somewhat in diagnostic accuracy compared with their accuracy on internal datasets.