Statistical process control in nursing research

Authors

  • Denise F. Polit,

    Corresponding author
    1. Humanalysis, Inc., 75 Clinton Street, Saratoga Springs, NY 12866
    2. Griffith University School of Nursing, Gold Coast, Australia
    • Humanalysis, Inc., 75 Clinton Street, Saratoga Springs, NY 12866.
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    • President and Professor.

  • Wendy Chaboyer

    1. Griffith University School of Nursing, Gold Coast, Australia
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    • Professor and Director, NHMRC Centre of Research Excellence in Nursing Interventions for Hospitalised Patients.


Abstract

In intervention studies in which randomization to groups is not possible, researchers typically use quasi-experimental designs. Time series designs are strong quasi-experimental designs but are seldom used, perhaps because of technical and analytic hurdles. Statistical process control (SPC) is an alternative analytic approach to testing hypotheses about intervention effects using data collected over time. SPC, like traditional statistical methods, is a tool for understanding variation and involves the construction of control charts that distinguish between normal, random fluctuations (common cause variation), and statistically significant special cause variation that can result from an innovation. The purpose of this article is to provide an overview of SPC and to illustrate its use in a study of a nursing practice improvement intervention. © 2011 Wiley Periodicals, Inc. Res Nurs Health 35:82–93, 2012

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