Improving Provider Adoption With Adaptive Clinical Decision Support Surveillance: An Observational Study

JMIR Human Factors
Sundas KhanThomas McGinn

Abstract

Successful clinical decision support (CDS) tools can help use evidence-based medicine to effectively improve patient outcomes. However, the impact of these tools has been limited by low provider adoption due to overtriggering, leading to alert fatigue. We developed a tracking mechanism for monitoring trigger (percent of total visits for which the tool triggers) and adoption (percent of completed tools) rates of a complex CDS tool based on the Wells criteria for pulmonary embolism (PE). We aimed to monitor and evaluate the adoption and trigger rates of the tool and assess whether ongoing tool modifications would improve adoption rates. As part of a larger clinical trial, a CDS tool was developed using the Wells criteria to calculate pretest probability for PE at 2 tertiary centers' emergency departments (EDs). The tool had multiple triggers: any order for D-dimer, computed tomography (CT) of the chest with intravenous contrast, CT pulmonary angiography (CTPA), ventilation-perfusion scan, or lower extremity Doppler ultrasound. A tracking dashboard was developed using Tableau to monitor real-time trigger and adoption rates. Based on initial low provider adoption rates of the tool, we conducted small focus groups with key ED provid...Continue Reading

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Citations

Aug 22, 2020·Yearbook of Medical Informatics·Ivana Jankovic, Jonathan H Chen
Jan 16, 2021·Journal of the American Medical Informatics Association : JAMIA·Carolyn PetersenAdam Wright
Dec 11, 2020·The Journal of Emergency Medicine·Brett ToddRonny Otero

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Software Mentioned

Tableau
Wells CDS
Wells

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