Know It When You See It: Identifying and Using Special Cause Variation for Quality Improvement
Alison R. Carroll, David Johnson
Abstract
In this month’s Hospital Pediatrics, Liao et\nal1 share their\nteam’s journey to improve the accuracy of their institution’s\nelectronic health record (EHR) problem list. They presented their results as\nstatistical process control (SPC) charts, which are a mainstay for visualization\nand analysis for improvers to understand processes, test hypotheses, and quickly\nlearn their interventions’ effectiveness. Although many readers might\nunderstand that 8 consecutive points above or below the mean signifies special\ncause variation resulting in a centerline “shift,” there are many\nmore special cause variation rules revealed in these charts that likely provided\nvaluable real-time information to the improvement team. These\n“signals” might not be apparent to casual readers when looking at\nthe complete data set in article form.