A Practical Guide to QI Data Analysis: Run and Statistical Process Control Charts

Author:

Winckler Britanny12,McKenzie Sheena3,Lo Huay-ying45

Affiliation:

1. aDivision of Hospital Medicine, Children’s Hospital of Orange County, Orange, California

2. bDepartment of Pediatrics, University of California, Irvine, Irvine, California

3. cAdvocate Children’s Hospital, Oak Lawn, Oak Lawn, Illinois

4. dDivision of Hospital Medicine, Texas Children’s Hospital, Houston, Texas

5. eDepartment of Pediatrics, Baylor College of Medicine, Houston, Texas

Abstract

Data analysis utilizing run charts and statistical process control (SPC) charts is a mainstay of quality improvement (QI) work. These types of time series analyses allow QI teams to evaluate patterns in data that may not be apparent with pre- and postintervention analysis. A run chart is most useful at the onset of a project when data points may be limited; points can be added prospectively to monitor for changes. An SPC chart is needed to determine if the system is “out of control,” indicating an instance of special cause variation, and is recommended for more robust data analysis. These charts are valuable tools in identifying patterns of change, but cannot indicate what caused the change. QI teams can further investigate significant patterns to identify the impact of interventions and promote continued change or sustainability. In this article, we will provide a practical guide to the basics of run and SPC charts, including how to create and interpret them. The reader can use the supplemental data tables to gain the skills needed to build their own charts with readily available software. Finally, we will review more specialized software options that can assist in creation of run and SPC charts.

Publisher

American Academy of Pediatrics (AAP)

Subject

Pediatrics,General Medicine,Pediatrics, Perinatology and Child Health

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