#RSNA 20– Constant Improvement Through Peer Knowing
” 20% of the research studies present 80% of the
Generally, the radiology community advocates peer review for quality control. The present pattern is to focus more on peer knowing, where gaining from peers in a constant enhancement mode ends up being more crucial than focusing on the (variety of) diagnostic errors.
Agfa HealthCare has developed a module that supports both peer evaluation and peer learning in its Enterprise Imaging (EI) platform. Just recently HealthManagement.org talked to Jan Kips and Danny Steels, Product Managers at Agfa HealthCare, to read more about this new module and how it can help facilitate learning in radiology by dealing with the imperfections of standard peer evaluation methods.
Agfa HealthCare is flipping the script on Peer Learning:
” The peer discovering workflow is entirely embedded in
a radiologists routine workflow.”
Uses the possibility to both instantly and manually set off peer evaluations;
Fully embeds the peer evaluation workflow in the radiology;
Anonymised, built-in feedback loops permit authors to gain from the recommendations of associates;
Devoted conference performance makes it possible for conversations on case and ability to follow-up on suggestions or procedure changes;
A highly configurable workflow permits clients to customize their workflow from traditional peer evaluation to a peer learning workflow with conferences and anything in between.
In the interview Jan and Danny also touch on the cultural impact and how a series of particular features of Agfas Peer Learning module can support a culture change and expand a real learning spirit in the health company.
Access the full interview here to find out more on:
Intrigued in more?
At the upcoming RSNA All Virtual we will be hosting a series of professional webinars on Peer Learning with Jan Kips and Danny Steels. Connect to go to and arrange your consultation with our experts today.
The full scope of the Agfa HealthCare Peer Learning approach;
How to embed it into the radiologist regular workflows for maximum effect;
How peer learning can be utilized for a 2nd opinion workflow.