It’s Time For Radiology To Adopt Business Intelligence Analytics


Radiology AnalyticsOne of radiology’s biggest thinkers, University of Chicago School of Medicine vice-chair of radiology informatics, Paul Chang, MD, wants radiologists to step up their game. Meaningful use requirements dictate the adoption of business intelligence analytics (BIA) for radiology. And you can’t improve what you don’t measure.

Measuring Efficiency Using Key Performance Indicators (KPIs)

According to Chang, radiology lags way behind other business models in the use of BIA, which includes dashboards, scorecards and other key performance indicators (KPIs). A KPI helps measure if you’re improving your processes, efficiencies and adding value to the product or service you provide.

Dashboards indicate whether you’re on target with respect to established goals. Picture Archiving and Communication Systems (PACS), Radiology Information Systems (RIS) and Electronic Medical Records (EMR) make it far easier for radiologists to do their job, but they don’t always measure the efficiency of their actions. BIA extracts information from medical imaging systems and organizes it into dashboards, graphical elements, etc., to demonstrate ways to improve workflow.

For example, providing a dashboard for report turnaround time can help keep the radiologist on a time track and is a KPI worth measuring. If he’s taking too long on an image or she’s taking too many breaks, a red light indicates that they are falling short of the projected goal. A green light means that they’re working efficiently and are on track.

Chang explains that strategic and tactical tools are “a must” in medical imaging if you want to identify whether you’re doing what you need to be doing operationally, 24/7. In addition, you must be able to measure if you’re adding value to your hospital, your patients and referring physicians. Chang views measuring efficiencies as a way to win both the battle and the war.

Staying on Track with Workflow Requirements

Quality indicators are additional KPIs that may need to integrate information from various departments. At the University of Chicago, Chang helped implement a pilot program that applies workflow improvements to scanning equipment. “The CT scanner programs itself,” he said. “The injector programs itself. After the scan is done, it knows about all the post-acquisition workflow requirements — sending stuff to PACs and 3D work stations, notifying transport.”

“These efficiencies are realized as improvements not only in radiology, but also length of stay, hospitalization, throughput in the clinics. We were able to realize about a 66- to 70-percent improvement in cycle time in our CT scanner by automating procedures that originally were done by humans,” he added.

How has your organization adopting, or how is your organization planning to adopt, business intelligence analytics for radiology?  I encourage you to share via a comment below.

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