Quality Improvement Methodology Facilitates Adherence to Echocardiogram Protocol Measurements

Abstract

Introduction: Local institutional echocardiogram protocols reflect standard measurements as per national guidelines, but adherence to measurements was inconsistent. This inconsistency led to variability in reporting and impacted the use of serial measurements for clinical decision-making. Therefore, we aimed to improve complete adherence to universal and protocol-specific measures for echocardiograms performed for first-time or cardiomyopathy studies from 60% to 90% from July 2019 to February 2020.

Methods: We included all sonographer-performed echocardiograms for first-time or cardiomyopathy protocol studies. We reviewed universal measures and protocol-specific measures for all included studies. We created a scoring system reflecting measurement completion. We used a control chart to measure compliance and established a baseline over 2 months. PDSA cycles over 5 months included interventions such as sonographer education, technical improvements to the measurement toolbar, and group and individual performance feedback.

Results: We reviewed over 4000 studies-the reporting of complete universal measures improved significantly from a median score of 60% to 93%. Protocol-specific measures for first-time studies also showed significant improvement from 62% to 90% adherence. Cardiomyopathy-specific measures demonstrated 87% adherence at baseline, which improved to 95% but then returned to baseline. Sonographer education and toolbar adjustment prompted special cause variation with further improvement following performance feedback. The universal and first-time protocol measures reached 90% adherence with sustained improvement for over 9 months.

Conclusions: We employed quality improvement methodology to improve complete adherence to echocardiographic protocol measurements, thereby facilitating echocardiographic quality and reporting consistency. We plan to spread these interventions to improve adherence to other protocols.

Fig. 1.

Key driver diagram. The key driver diagram demonstrates the SMART (specific, measurable, achievable, reliable, and timely) aim in the first column. The second column describes the key drivers of change, and the third column includes the interventions made with the level of reliability listed. LOR, level of reliability.

Fig. 2.

Upgraded toolbar for universal measures. The left-sided panel shows the previous toolbar for universal measures with multiple different colors and several unnecessary measurements. The right-sided panel shows the upgraded toolbar with only the necessary measurements included. This intervention prompted special cause variation in our adherence to universal measures.

Fig. 3.

Control chart demonstrating special cause variation in adherence to universal measures with improvement from 60% to 93%. The yellow boxes indicate interventions. The green box indicates the established goal date for improved adherence. The green arrow indicates the direction of anticipated change. The n value is the total number of attainable points for each week.

Fig. 4.

Pareto Chart presenting the most common of the universal measures missed between February and November 2020.

Fig. 5.

Control chart demonstrating special-cause variation in first-time study protocol measures with improvement from 62% to 90%. The yellow boxes indicate interventions. The green box indicates the established goal date for improved adherence. The green arrow indicates the direction of anticipated change. The n value is the total number of attainable points for each week.

Fig. 6.

Control chart demonstrating initial special cause variation for cardiomyopathy protocol measures from a baseline of 87% to 95% adherence, which subsequently returned to baseline. The yellow boxes indicate interventions. The green box indicates the established goal date for improved adherence. The green arrow indicates the direction of anticipated change. The n value is the total number of attainable points for each week.