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Clin Perinatol. 2017 Sep;44(3):627-644. doi: 10.1016/j.clp.2017.05.011.

Using Statistical Process Control to Drive Improvement in Neonatal Care: A Practical Introduction to Control Charts.

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Department of Neonatology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA 02215, USA. Electronic address:
Perinatal Institute and James M. Anderson Center for Health Systems Excellence, Cincinnati Children's Hospital Medical Center, University of Cincinnati School of Medicine, 3333 Burnet Avenue, MLC 7009, Cincinnati, OH 45229, USA.


Quality improvement (QI) is based on measuring performance over time, and variation in data measured over time must be understood to guide change and make optimal improvements. Common cause variation is natural variation owing to factors inherent to any process; special cause variation is unnatural variation owing to external factors. Statistical process control methods, and particularly control charts, are robust tools for understanding data over time and identifying common and special cause variation. This review provides a practical introduction to the use of control charts in health care QI, with a focus on neonatology.


Common cause variation; Control chart; Quality improvement; Special cause variation; Statistical process control

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