Quality Metrics and Data-Driven Improvement (2026)-Understanding and Analyzing Quality Data

Understanding and Analyzing Quality Data

Video Transcription

Video Summary

The speaker, Gautaman Ganabhushanam from Yale Radiology, explains how to understand and analyze quality data using charts. He reviews key visual tools: run charts for tracking change over time, control charts for distinguishing common versus special cause variation, histograms for showing data distribution, Pareto charts for identifying the most important causes, and scatter plots for examining relationships between variables. He emphasizes that charts make data clearer than tables and support quality improvement by revealing trends, variation, and outcomes. He also notes that correlation does not imply causation.

Keywords

run charts

control charts

histograms

Pareto charts

scatter plots