Data and Measurement

For effective quality improvement work, data is needed to evaluate if changes tested are resulting in improvement. Quality improvement data is often gathered on a set of measures. Outcome, process and balancing measures promote understanding of the impact of changes on the system. Data is also important to understand the variation in a process, and to monitor the process over time.

The resources below are designed to help you:

1. Understand how to best visualize your data
2. Appreciate the limitations of data
3. Provide instruction on data gathering and analysis

Resources

Read	Variation: Common and Special Cause Variation Managing for Daily Improvement Boards: How to create a MDI Board EPIC Reporting Manual (provides detailed info on how to protect PHI on pages 1, 9-10) Measuring Quality Improvement in Healthcare: A Guide to Statistical Process Control Applications – This book covers practical applications of the tools and techniques of statistical process control (SPC), including control charts, in healthcare settings. The core of the book is a set of 12 case studies that show how to apply statistical thinking to health care process, and when and how to use different types of control charts. *This link requires you to enter your onyen and password before accessing the online copy.
Use	A Model for Measuring Quality Care (NHS Improvement brief) (outcome, process, structure and balancing measures) Data Sources: (EPIC) (Business Objects) How to get Access to EPIC Control Chart Overview: guidance for choosing the right type of control chart Creating Control Charts with QI Macros Run Chart Template Pareto Charts Job Aid Graph Formatting Best Practices
Watch	Correlation: this video demonstrates why correlation does not imply causality (Video – 10:44)