Publication date: Dec 20, 2024
The adherence of clinicians to clinical practice guidelines is known to be low, including for the management of COVID-19, due to their difficult use at the point of care and their complexity. Clinical decision support systems have been proposed to implement guidelines and improve adherence. One approach is to permit the navigation inside the recommendations, presented as a decision tree, but the size of the tree often limits this approach and may cause erroneous navigation, especially when it does not fit in a single screen. We proposed an innovative visual interface to allow clinicians easily navigating inside decision trees for the management of COVID-19 patients. It associates a multi-path tree model with the use of the fisheye visual technique, allowing the visualization of large decision trees in a single screen. To evaluate the impact of this tool on guideline adherence, we conducted a randomized controlled trial in a near-real simulation setting, comparing the decisions taken by medical trainees using Orient-COVID with those taken with paper guidelines or without guidance, when performing on six realistic clinical cases. The results show that paper guidelines had no impact (p=0. 97), while Orient-COVID significantly improved the guideline adherence compared to both other groups (p
Concepts | Keywords |
---|---|
Clinicians | COVID-19 |
Covid19 | Decision tree |
Erroneous | Simulation trial |
Fisheye | |
Trees |
Semantics
Type | Source | Name |
---|---|---|
disease | MESH | COVID19 |