title: How do you know that your care is improving? Part II: Using control charts to learn from your data.
abstract: This article builds on my article in the January 2002 issue of JACM on the use of run charts to analyze data variation and document process improvement. It describes a more powerful tool than the run chart for analyzing variation and measuring process improvement, namely, the control chart developed by Walter Shewhart. This article first explains the basic elements of a control chart, the tests for detecting a special cause variation, and how to choose the best control chart for the type of data being collected. It concludes with one case study using a control chart to document a successful intervention and some suggestions regarding computer software.
authors: R. G. Carey and Associates, Park Ridge, Illinois, USA.
authors: Raymond G
authors: RG
authors: Carey
mesh_terms: D003625:Data Collection; D003627:Data Interpretation, Statistical; D017598:Efficiency, Organizational / Q000706:statistics & numerical data; D005568:Forms and Records Control; D006801:Humans; D010043:Outcome and Process Assessment, Health Care / Q000706:statistics & numerical data*; D011785:Quality Assurance, Health Care / Q000379:methods*; D014481:United States