Pareto charts, scatter plots, and bubble charts

Data visualization is essential for exploring potential cause-effect relationships, prioritizing interventions, and communicating findings in healthcare quality improvement. This paper uses clinical examples to explore three key tools-Pareto charts, scatter plots, and bubble charts-that help teams analyze system variables and patient outcomes. Pareto charts highlight the most significant contributors to a system's processes and outcomes using the 80/20 principle. We illustrate their use in improving the timing of antibiotic administration in a pediatric emergency department. Scatter plots reveal correlations between two variables. Using the same example, we show how these plots can assess the impact of factors such as patient age on antibiotic administration timing. Bubble charts enhance scatter plots by visualizing a third variable through bubble size. Here, we compare antibiotic timing with each provider's years of experience and number of patients seen. Use of these tools enables quality improvement teams to identify trends, target interventions, and effectively communicate system performance. Regular practice with these tools can enhance quality improvement efforts and patient outcomes.