Optimizing radiologist operations.
Unclear case prioritization
Time-sensitive cases were difficult to identify and route efficiently.
High cognitive load
Teams lacked visibility into balancing diagnostic work across radiologists and locations.
Outdated interface designs
Legacy interaction models created friction throughout daily diagnostic workflows.
Original radiologist platform
Original radiologist platform
Pattern dependency
Memorized queue patterns reduced workflow clarity and consistency.
Competing cases
Urgent cases competed against routine studies within dense imaging queues.
Decentralized data
Important case details were spread across multiple screens and interaction points.
Staffing blindspots
Coverage availability and workload balancing lacked centralized visibility.
Workflow variability
Imaging sites developed inconsistent workflow patterns in the same platform.
Offline coordination
Staffing case redistribution relied heavily on communication outside the platform.
Business Drivers
Prioritization matrix
Refining high-impact key screens.
Reimagined legacy interfaces to reduce cognitive load, improve prioritization, and support growing diagnostic demand.
Radiologist worklist
Capacity planning scenario
Forecast modeling
Radiologist Worklist
Vertical Case Screen
Demand Capacity Management
Scaling radiology operations under pressure.
Imaging demand surged during the pandemic, incentivizing healthcare systems
to rapidly expand and coordinate distributed radiology operations at scale.
