To reduce patient exposure to radiation, the University of Washington School of Medicine is taking advantage of big data.
Dose tracking technology adopted by the medical center can pull information from multiple imaging devices, then sort it into a database where it can be sliced and diced, according to InformationWeek. UW Medical Director William Shuman said that the data helps to "validate" its imaging efforts, in addition to pinpointing areas in need of improvement.
For instance, he said, when the hospital recently started performing dual-energy CT scans of patient livers, he wanted to know if the process actually resulted in lower radiation use. Within 20 seconds, he said, he learned that the new procedure resulted in lower dosage used than for single energy CT scans.
"I was very happy we were getting more diagnostic information with more information," Shuman told InformationWeek.
Prior efforts to pull similar data used to take as long as a few weeks, according to the article, because data from the tools used to be stored in disparate, disconnected databases.
The use of data analytics is becoming an increasingly important tool in the effort to follow and reduce radiation exposure. Recently FierceMedicalImaging ran a special report on data analytics and medical imaging in which Katherine Andriole, professor and director of imaging informatics at Harvard Medical School and Brigham and Women's Hospital in Boston, talked about analytics and tracking radiation exposure.
"It helps us see whether our exams are within certain ranges that are acceptable," Andriole said. "And if we see a bump in that curve we can drill down into specific exams and see what happened. Why did that protocol have a much higher radiation dose? Perhaps this was a research study, or maybe it was an in appropriate study."
To learn more:
- check out the article in InformationWeek
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