How do you know that your care is improving? Part II: Using control charts to learn from your data.
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.
Carey
Raymond G
RG
R. G. Carey and Associates, Park Ridge, Illinois, USA.
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