December 2, 2010 – Radiologists can benefit from advanced analytics and business intelligence applications, says Paul Nagy, a researcher at the University of Maryland's School of Medicine.
Speaking at RSNA 2010 this week in Chicago, Nagy described a dashboard in use at the academic medical center. It captures a variety of business and clinical metrics applicable to the radiology department. These include patient waiting times, retake rates for various modalities, and reporting timelines for physicians reading studies. Nagy cautioned against using analytics that are too narrowly focused, such as radiologist productivity alone. The quality of images and reports are equally important, he said, as is the turnaround time to referring physicians who ordered the tests in the first place.
According to Nagy, the "age of analytics" began in 2006 with the widespread advent of data reporting and mining tools. He noted that some PACS and RIS vendors have BI capabilities built into their systems, but advised delivery organizations to look for vendors that can combine data from those and other systems. U-Maryland's own dashboard contains multiple performance measures, each displayed with a color-coded meter that highlights times when performance indicators--such as physician reporting time--are slipping into a danger zone.
The timeliness of data presentation is another critical factor in performance improvement, he noted. For example, the medical center used to provide the radiology department chair a monthly report of which physicians were behind in signing their charts. Now that information is presented every three days, and rather than presenting it at a department meeting, the chairman calls individual doctors who are behind in completing documentation. That simple step resolved the problem, Nagy said.
And by analyzing traffic patterns in the waiting room, the department was able to streamline delivery of outpatient mammograms. "If you ignore quality, you can only improve so much," Nagy said.
This story originally appeared on Health Data Management.
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