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      Run Charts Revisited: A Simulation Study of Run Chart Rules for Detection of Non-Random Variation in Health Care Processes

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      PLoS ONE

      Public Library of Science

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          Abstract

          Background

          A run chart is a line graph of a measure plotted over time with the median as a horizontal line. The main purpose of the run chart is to identify process improvement or degradation, which may be detected by statistical tests for non-random patterns in the data sequence.

          Methods

          We studied the sensitivity to shifts and linear drifts in simulated processes using the shift, crossings and trend rules for detecting non-random variation in run charts.

          Results

          The shift and crossings rules are effective in detecting shifts and drifts in process centre over time while keeping the false signal rate constant around 5% and independent of the number of data points in the chart. The trend rule is virtually useless for detection of linear drift over time, the purpose it was intended for.

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          Most cited references 1

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          Plotting basic control charts: tutorial notes for healthcare practitioners.

          There is considerable interest in the use of statistical process control (SPC) in healthcare. Although SPC is part of an overall philosophy of continual improvement, the implementation of SPC usually requires the production of control charts. However, as SPC is relatively new to healthcare practitioners and is not routinely featured in medical statistics texts/courses, there is a need to explain the issues involved in the selection and construction of control charts in practice. Following a brief overview of SPC in healthcare and preliminary issues, we use a tutorial-based approach to illustrate the selection and construction of four commonly used control charts (xmr-chart, p-chart, u-chart, c-chart) using examples from healthcare. For each control chart, the raw data, the relevant formulae and their use and interpretation of the final SPC chart are provided together with a notes section highlighting important issues for the SPC practitioner. Some more advanced topics are also mentioned with suggestions for further reading.
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            Author and article information

            Contributors
            Role: Editor
            Journal
            PLoS One
            PLoS ONE
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, USA )
            1932-6203
            2014
            25 November 2014
            : 9
            : 11
            Affiliations
            [1 ]Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
            [2 ]University of Aalborg, Danish Center for Healthcare Improvements, Department of Business and Management, Aalborg, Denmark
            Cardiff University, United Kingdom
            Author notes

            Competing Interests: The authors have declared that no competing interests exist.

            Conceived and designed the experiments: JA AVO. Performed the experiments: JA AVO. Analyzed the data: JA AVO. Contributed reagents/materials/analysis tools: JA AVO. Wrote the paper: JA AVO.

            Article
            PONE-D-14-08548
            10.1371/journal.pone.0113825
            4244133
            25423037

            This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

            Page count
            Pages: 13
            Funding
            The authors have no support or funding to report.
            Categories
            Research Article
            Computer and Information Sciences
            Computerized Simulations
            Engineering and Technology
            Production Engineering
            Production Control
            Medicine and Health Sciences
            Epidemiology
            Epidemiological Methods and Statistics
            Epidemiological Statistics
            Health Care
            Health Care Quality
            Health Services Research
            Quality of Care
            Physical Sciences
            Mathematics
            Statistics (Mathematics)
            Statistical Methods
            Statistical Hypothesis Testing
            Statistical Inference
            Statistical Theories
            Research and Analysis Methods
            Mathematical and Statistical Techniques

            Uncategorized

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