Impact on clinical guideline adherence of Orient-COVID, a clinical decision support system based on dynamic decision trees for COVID19 management: A randomized simulation trial with medical trainees

Mouin Jammal; Antoine Saab; Cynthia Abi Khalil; Charbel Mourad; Rosy Tsopra; Melody Saikali; Jean-Baptiste Lamy

doi:10.1016/j.ijmedinf.2024.105772

Impact on clinical guideline adherence of Orient-COVID, a clinical decision support system based on dynamic decision trees for COVID19 management: A randomized simulation trial with medical trainees

Int J Med Inform. 2024 Dec 20:195:105772. doi: 10.1016/j.ijmedinf.2024.105772. Online ahead of print.

Authors

Mouin Jammal¹, Antoine Saab², Cynthia Abi Khalil³, Charbel Mourad⁴, Rosy Tsopra⁵, Melody Saikali⁶, Jean-Baptiste Lamy⁷

Affiliations

¹ Department of Internal Medicine, Lebanese Hospital Geitaoui-UMC, Beirut, Lebanon. Electronic address: mouinjammal@yahoo.fr.
² Quality and Patient Safety Department, Lebanese Hospital Geitaoui-UMC, Beirut, Lebanon; INSERM, Université Sorbonne Paris Nord, Sorbonne Université, LIMICS, 75006 Paris, France. Electronic address: antoine_saab@outlook.com.
³ Nursing Administration, Lebanese Hospital Geitaoui-UMC, Beirut, Lebanon; INSERM, Université Sorbonne Paris Nord, Sorbonne Université, LIMICS, 75006 Paris, France. Electronic address: Cynthiakjammal@outlook.com.
⁴ Department of Medical Imaging, Lebanese Hospital Geitaoui-UMC, Beirut, Lebanon. Electronic address: charbel.j.mourad@hotmail.com.
⁵ Université Paris Cité, Sorbonne Université, Inserm, Centre de Recherche des Cordeliers, F-75006 Paris, France; Department of Medical Informatics, AP-HP, Hôpital Européen Georges-Pompidou, F-75015 Paris, France. Electronic address: rosytsopra@gmail.com.
⁶ Quality and Patient Safety Department, Lebanese Hospital Geitaoui-UMC, Beirut, Lebanon. Electronic address: melodysaikali@hotmail.com.
⁷ INSERM, Université Sorbonne Paris Nord, Sorbonne Université, LIMICS, 75006 Paris, France. Electronic address: jean-baptiste.lamy@inserm.fr.

PMID: 39721112
DOI: 10.1016/j.ijmedinf.2024.105772

Abstract

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 trainees 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.

Keywords: COVID-19; Clinical decision support system; Decision tree; Simulation trial.