Data-driven engineering improves radiology productivity

Using objective data-oriented engineering processes to replace traditional workflow monitoring can increase radiology productivity, according to a paper presented at the 2005 Society for Computer Applications in Radiology meeting.

A product development process that emphasizes the subjective opinions of a few high-end users and engineers rather than objective data gathered through real-life use of a product or application can lead to unwieldy designs that don't fit into a typical radiologist's workflow.

The key to efficiently improving design is automatic tracking, capturing, and profiling of all keyboard, mouse, and head-eye movements the radiologist makes at the workstation. Computers record and use this data for further analysis to fine-tune workflow, said Prakash Mahesh, Ph.D., of GE Healthcare.

"Data-driven engineering is where feature, design, and workflow decisions are made based on true quantitative data collected continuously from the end user," Mahesh said.

Data collected automatically can then be used to seed design decisions, incorporating those areas of the product such as buttons, menus, and imaging controls that are used the most and minimizing or eliminating tools used the least.

"Performance optimizations, feature enhancements, and workflow optimizations can all be made based on empirical data," he said.

Traditional ways of capturing radiology workflow involve monitoring the radiologist in a reading room and noting the steps taken to read images. But, like quantum physics, the mere act of observing can affect the data.

"Studies have shown that monitoring radiologists in a reading room can affect the data gathered because the radiologist is conscious of being watched and may not follow a normal course of action," Mahesh said.

Also, the amount of data collected is restricted to the duration of the observation.

"Data-driven engineering is a unique approach in handling radiology efficiency and productivity," he said.