• Thomas R Vetter and Douglas Morrice.
• From the Department of Surgery and Perioperative Care, Dell Medical School at the University of Texas at Austin, Austin, Texas.
• Anesth. Analg. 2019 Feb 1; 128 (2): 374-382.

AbstractA novel intervention or new clinical program must achieve and sustain its operational and clinical goals. To demonstrate successfully optimizing health care value, providers and other stakeholders must longitudinally measure and report these tracked relevant associated outcomes. This includes clinicians and perioperative health services researchers who chose to participate in these process improvement and quality improvement efforts ("play in this space"). Statistical process control is a branch of statistics that combines rigorous sequential, time-based analysis methods with graphical presentation of performance and quality data. Statistical process control and its primary tool-the control chart-provide researchers and practitioners with a method of better understanding and communicating data from health care performance and quality improvement efforts. Statistical process control presents performance and quality data in a format that is typically more understandable to practicing clinicians, administrators, and health care decision makers and often more readily generates actionable insights and conclusions. Health care quality improvement is predicated on statistical process control. Undertaking, achieving, and reporting continuous quality improvement in anesthesiology, critical care, perioperative medicine, and acute and chronic pain management all fundamentally rely on applying statistical process control methods and tools. Thus, the present basic statistical tutorial focuses on the germane topic of statistical process control, including random (common) causes of variation versus assignable (special) causes of variation: Six Sigma versus Lean versus Lean Six Sigma, levels of quality management, run chart, control charts, selecting the applicable type of control chart, and analyzing a control chart. Specific attention is focused on quasi-experimental study designs, which are particularly applicable to process improvement and quality improvement efforts.

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