Efficient compliance. Eliminate waste. Improve quality. Bigger margins.
Foundations™ Peer Review has replaced the age-old paradigm of the peer review effort with data-driven automation. No more administrative or clinical effort waste. Selection and assignment model, worklists, and image make radiologists workflow easy and fast, saving time and energy to focus on what matters: clinical review of images and diagnostic results.
- Workflow automation
- Selection and assignment
- Confidential, trust-worthy quality review and positive peer-learning environment
Cases are automatically selected, appointed, and sent to radiologists without manual, human intervention, lowering administrative costs, freeing up staff and improving margins. Reviews are conducted anonymously, eliminating bias and promoting a positive, engaging peer review and learning culture. Additional related workflow automation improves patient case reviews and follow-ups.
Additional Features
- Seamless Integration – Foundations™ Peer Review works with existing applications and organization structure, driving adoption and benefits without disruption.
- Flexible Assignment Model – Foundations™ Peer Review allows for constraints to account reviewer-to-reviewee eligibility, including assignments with a machine-learning approach.
- Robust Selection Model – The selection model in Foundations™ Peer Review can be configured for randomized selection at par with national approaches as well as risk-based selection for internal quality reviews. This approach assures compliance fairness as well as a separate internal learning approach in the same environment.