Archive (2016–2006)

Control Charts in Healthcare Quality Improvement

Journal: Methods of Information in Medicine
Subtitle: A journal stressing, for more than 50 years, the methodology and scientific fundamentals of organizing, representing and analyzing data, information and knowledge in biomedicine and health care
ISSN: 0026-1270

Focus Theme: Medical Imaging High Performance Methods
Guest Editors: C. Kulikowski, L. Gong

Issue: 2012 (Vol. 51): Issue 3 2012
Pages: 189-198

Control Charts in Healthcare Quality Improvement

A Systematic Review on Adherence to Methodological Criteria

Review Article

A. Koetsier (1), S. N. van der Veer (1), K. J. Jager (1), N. Peek (1), N. F. de Keizer (1)

(1) Department of Medical Informatics, Academic Medical Center, Amsterdam, The Netherlands


process assessment (health care), Statistical process control, healthcare quality improvement, quality improvement methodologies


Objectives: Use of Shewhart control charts in quality improvement (QI) initiatives is increasing. These charts are typically used in one or more phases of the Plan Do Study Act (PDSA) cycle to monitor summaries of process and outcome data, abstracted from clinical information systems, over time. We summarize methodological criteria of Shewhart control charts and investigate adherence of published QI studies to these criteria.

Methods: We searched Medline, Embase and CINAHL for studies using Shewhart control charts in QI processes in direct patient care. We extracted methodological criteria for Shewhart control charts, and for the use of these charts in PDSA cycles, from textbooks and methodological literature.

Results: We included 34 studies, presenting 64 control charts of which 40 control charts plotted two phases of the PDSA cycle. The criterion to use 10–35 data points in a control chart was least adhered to (48.4% non-adherence). Other criteria were: transformation of the data in case of a skewed distribution (43.7% non adherence), when comparing data from two phases of the PDSA cycle the Plan phase (the first phase) needs to be stable (40.0% non-adherence), using a maximum of four different rules to detect special cause variation (14.1% non-adherence), and setting control limits at three standard deviations from the mean (all control charts adhered).

Conclusion: There is room for improvement with regard to the methodological construction of Shewhart control charts used in QI processes. Higher adherence to all methodological criteria will decrease the risk of incorrect conclusions about the process being monitored.

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