Quality Metrics and Data-Driven Improvement (2026)-Using Data to Identify Areas for Improvement

Using Data to Identify Areas for Improvement

Video Transcription

Video Summary

The session explains how data helps identify areas for improvement in quality improvement projects. Using ultrasound, CT, and imaging turnaround examples, the speaker shows that jumping to solutions without data can fail. Tools discussed include process maps/flowcharts to visualize workflow and find bottlenecks, fishbone diagrams to brainstorm causes, histograms to examine turnaround-time distributions, Pareto charts to prioritize the biggest delay sources, and FMEA to proactively assess risk using severity, occurrence, and detection scores. The key message is to use data to choose high-impact interventions and avoid wasting effort on assumptions.

Keywords

quality improvement

data analysis

workflow bottlenecks

turnaround time

FMEA