Ginea Qualls, Senior Clinical System Engineer, Radiology Associates. Hosted by Mike Moore. Runtime 27:15.
Ginea Qualls did not set out to work in radiology. She started at nineteen doing accounts receivable at a bottled-water company, back before the business even had an IT department, and taught herself the work by asking how things were done. Twenty-five-plus years later she runs the enterprise imaging that lets an independent practice read close to a million studies a year for around two dozen hospitals and a hundred-plus clinics across Arkansas.
The heart of the conversation is orchestration. When a study is ordered, the images, the HL7 order, and the priors all have to arrive and marry up before a radiologist ever sees the case. Ginea walks through how her team routes that traffic through a DICOM router and an HL7 engine into the worklist, then filters it by credential and subspecialty so an MSK study reaches an MSK reader, and a suspected stroke jumps to the top of the list against the clock. Worklists are ordered by priority, then time remaining against the SLA, then class, so the most urgent read surfaces first.
She is candid about where it breaks. Priors are the recurring problem, not because the prior is hard, but because getting the right prior to marry up to the current study across dozens of unrelated facilities is. A patient may start care at a rural hospital and finish in Little Rock, and if the record does not match on something as small as a name, the read slows down. Bad data and malformed DICOM are the other everyday puzzle.
On AI, Ginea is practical. The clearest win today is prioritization: an AI flag on an outpatient head CT that spots a brain bleed can elevate a study that would otherwise sit for hours. The radiologist still makes every diagnosis. She is also turning AI on her own operation, analyzing worklist data to find where prior requests cluster and driving that rate down site by site. Her read on the next few years is that agents will catch missing pieces before a human has to, so the study arrives cleaner and the radiologist spends their time reading, not chasing.
12:01 The invisible engineer. "If everything's working well, people don't know I exist." The best sign the imaging is working is that nobody thinks about the person keeping it running.
12:54 Why priors matter. "You wouldn't open a book and start reading in the middle." A radiologist needs the earlier image to see whether what is in front of them has grown or shrunk, and getting that prior to line up across unrelated facilities is where most of the detective work happens.
17:34 AI that prioritizes, not diagnoses. An outpatient head CT that turns up a brain bleed would normally sit in a lower-priority queue. An AI flag moves it to the top, and the radiologist still makes the call. "It's not taking that role away. It's enhancing that role."
Ginea Qualls is the Senior Clinical System Engineer at Radiology Associates, P.A. She has more than twenty-five years in IT, with the last fifteen-plus focused on healthcare and radiology, and leads enterprise imaging, workflow design, system implementations, and AI integration for the practice.
Radiology Associates is Arkansas's largest independent, physician-owned radiology practice and one of the oldest continuously operating medical practices in the country. The group reads more than 900,000 studies a year, operates from roughly 35 locations, and provides subspecialty reads across around two dozen Arkansas hospitals and a hundred-plus clinics with a team of fellowship-trained radiologists.
Right study, right radiologist, right time walks through the routing, the priors problem, and the standard worth borrowing from how Ginea runs the work before the read.
Flight Path is Mach7's show about where healthcare imaging is going and the people helping it get there, hosted by Mike Moore. New episodes every other Tuesday.
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