  Background: 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. Methods: 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 students using Orient-COVID with those
taken with paper guidelines or without guidance, when performing on six
realistic clinical cases. Results: 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<0.0003). A significant impact of
Orient-COVID was identified on several key points during the management of
COVID-19: ordering troponin lab tests, prescribing anticoagulant and oxygen
therapy. A multifactor analysis showed no difference between male and female
participants. Conclusions: The use of an interactive decision tree for the
management of COVID-19 significantly improved the clinician adherence to
guidelines. Future works will focus on the integration of the system to
electronic health records and on the adaptation of the system to other clinical
conditions.
