Why traditional statistical process control charts for attribute data should be viewed alongside anxmr-chart

Abstract

The use of statistical process control (SPC) charts in healthcare is increasing. The general advice when plotting SPC charts is to begin by selecting the right chart. This advice, in the case of attribute data, may be limiting our insights into the underlying process and consequently be potentially misleading. Given the general lack of awareness that additional insights may be obtained by using more than one SPC chart, there is a need to review this issue and make some recommendations. Under purely common cause variation the control limits on the xmr-chart and traditional attribute charts (eg, p-chart, c-chart, u-chart) will be in close agreement, indicating that the observed variation (xmr-chart) is consistent with the underlying Binomial model (p-chart) or Poisson model (c-chart, u-chart). However, when there is a material difference between the limits from the xmr-chart and the attribute chart then this also constitutes a signal of an underlying systematic special cause of variation. We use one simulation and two case studies to demonstrate these ideas and show the utility of plotting the SPC chart for attribute data alongside an xmr-chart. We conclude that the combined use of attribute charts and xmr-charts, which requires little additional effort, is a useful strategy because it is less likely to mislead us and more likely to give us the insight to do the right thing.

Improving hydration of care home residents by increasing choice and opportunity to drink: A quality improvement study

“…The mean and the control limits were recalculated if any special cause variations occurred. 22 The rationale for using these measures was that if fluid intakes increased, the incidence and/or severity of constipation and infections should decrease with concomitant reduction of laxative and antibiotic use.…”

Statistical process control charts for attribute data involving very large sample sizes: a review of problems and solutions

“…Where the control limits are broadly similar, then the underlying process is dominated by within-subgroup sampling variability, and the traditional attribute chart is likely to be adequate. Our preferred approach is for the analyses to incorporate the combined charting strategy23 because it is relatively straightforward to carry out within the SPC paradigm, and is likely to help maximise our understanding of the voice of the process while minimising the risk of being misled with attribute data 23. However, if we have to select only one SPC chart, then we suggest that this choice is better made after, not before, insights from the combined charting strategy.…”

Process Control Charts in Falls Prevention: The Experience of the Local Healthcare Authority of Romagna, Italy

“…The relevance of SPC in the healthcare context is confirmed in reviews by Benneyan et al [4], Thor et al. [5], Noyez [6] and Woodall et al [7]; in books by Carey [8], Winkel and Zhang [9], Faltin et al [10], Morton et al [11], and Melo and Beck [12]; and in methodological notes by Mohammed et al [13], Mohammed and Worthington [14] and Mohammed et al [15].…”