Dashboards bring predictive modeling to healthcare management

Like so many other types of information technology, analytics is maturing, from "reactive" business intelligence that informs decisions based on historical data to predictive modeling that essentially acts as "decision support for management"; this according to Paul Nagy, associate professor of diagnostic radiology and nuclear medicine in the University of Maryland's Department of Diagnostic Imaging.

Nagy, who presented at the Radiological Society of North America's annual conference in Chicago last week, said that a good data dashboard needs metrics on volume, performance and quality to help practitioners and decision makers adapt to changing conditions. In radiology, information should come from multiple sources, including RIS, PACS, CPOE and speech recognition systems, according to Nagy, and should be presented in graphical form. At the University of Maryland, the data mining helps to build a culture of transparency and accountability. "We need this culture to raise awareness about our problems and align key players to solve the problems of radiology," said Nagy, according to CMIO.

Nagy added that radiology systems vendors are starting to take note of the potential of digital dashboards and are developing new features around predictive modeling.

To learn more:
- check out this CMIO story

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