Many know Sol Radiology as the Southern California-based practice that, in this decade, grew from three radiologists to 45 in only three years. But other key indicators of Sol’s development might be the pieces from which presently small practices stand to learn the most.
When soaring imaging volumes began to exacerbate workload inequity and drive physician burnout, the leadership team at one prominent radiology practice found the root cause easy to isolate: operational fragmentation.
Radiology is rethinking reporting. Legacy systems are being swapped out in favor of intuitive, standardized, AI-powered tools. Greater automation is driving quantifiable improvements into both clinical outcomes and business metrics. Stated another way, radiology reporting is having a moment.
A referring physician orders an MRI of the lumbar spine and hits send. That order lands at three, sometimes four, outpatient imaging centers simultaneously. The center that contacts the patient first books the appointment. The rest miss out on the revenue.
3D surface modeling and virtual surgical planning are expanding radiology’s contribution to multidisciplinary teams. Together, AI-driven interpretation and 3D-enabled clinical collaboration represent two distinct, complementary forces shaping the next decade of radiology.
As an early adopter of speech recognition technology in 2000, Richard H. Wiggins, III, MD, CIIP, FSIIM, witnessed a stunning reduction in turnaround times (TAT) at the University of Utah Health Care, Salt Lake City.
Breast-imaging interpretations by telemedicine? More than a few have said that it couldn’t be done—or, at least, that it couldn’t be done well.
When we began working with our first radiology clients well over 10 years ago, we assumed they would be similar to most other medical and law groups for which we had consulted.
Of all scenarios in radiology that call for lightning-fast turnaround times coupled with absolute accuracy, few present the pressure of serving as the radiology group on call for in-season sports-injury studies.
What do you do with legacy data-storage applications containing near-antique patient information—so old it hasn’t been accessed in up to 20 years—that may yet be needed for legal, financial, clinical or population-management purposes?
Hospital CIOs now recognize that it’s no longer a question of whether vendor neutral archive (VNA) is a technology they should consider, but rather when is the right time to introduce VNA to their IT organization.
It’s T-minus two and a half years, give or take, on the liftoff of Meaningful Use stage 3. In 2018, every eligible hospital and eligible professional must attest to a single set of eight objectives—or suffer reduced Medicare/Medicaid reimbursements—in what is expected to be the final and definitive MU stage.
Every hospital-based radiology department in the U.S. knows it needs to reduce costs while improving care—now, not later on down the road—but only the most focused and forward-looking manage to pull off the feat one day and, the next, secure its sustainability for many years to come.
