[Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements]: Discussion

Woodall, William H.; Maragah, Hazem D.

doi:10.2307/1269837

Cited by 14 publications

(4 citation statements)

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“…Sixth, the EWMA and VLAD analyses have some limitations. A disadvantage of the EWMA is that it can be slow to react to an increase in mortality if the observed mortality is close to the threshold (inertia problem) [30], although this is not a common occurrence [31]. The main limitation of VLAD is that a good run of results may mask a subsequent poor run, which will mean that an excess of deaths is needed to cross the control limit [32].…”

Section: Strengths and Limitationsmentioning

confidence: 99%

Comparison of Critical Care Occupancy and Outcomes of Critically Ill Patients during the 2020 COVID-19 Winter Surge and 2009 H1N1 Influenza Pandemic in Australia

et al. 2021

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Availability of data and material and code availability: A de-identified dataset will be made available upon request to the corresponding authors one year after the publication of this study. The request must include a statistical analysis plan. The code is available upon request.Author's Contributions: All authors designed the study and were involved in collecting the data with the help of the study collaborators. Dr. Serpa Neto did the analyses. Drs. Serpa Neto, Burrell, Bailey, Cooper, Bellomo and Udy drafted the manuscript. All authors revised and approved the final draft.

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Section: Strengths and Limitationsmentioning

confidence: 99%

Comparison of Critical Care Occupancy and Outcomes of Critically Ill Patients during the 2020 COVID-19 Winter Surge and 2009 H1N1 Influenza Pandemic in Australia

et al. 2021

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“…A disadvantage of the RA-EWMA is that it can be slow to react to an increase in mortality if the EWMA(observed) is close to the threshold (inertia problem),20 although Lucas and Saccucci point out that this is not a common occurrence 20 21. Nevertheless, we guard against inertia by using the RA-EWMA as part of a co-ordinated safety and data analysis structure that includes analysis of index events (mortality review, sentinel events and near misses) and process reviews.…”

Section: Discussionmentioning

confidence: 99%

Exponentially weighted moving average charts to compare observed and expected values for monitoring risk-adjusted hospital indicators

Cook

Coory

Webster

2011

BMJ Quality & Safety

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OBJECTIVE To introduce a new type of risk-adjusted (RA) exponentially weighted moving average (EWMA) chart and to compare it to a commonly used type of variable life adjusted display chart for analysis of patient outcomes. DATA Routine inpatient data on mortality following admission for acute myocardial infarction, from all public and private hospitals in Queensland, Australia. METHODS The RA-EWMA plots the EWMA of the observed and predicted values. Predicted values were obtained from a logistic regression model for all hospitals in Queensland. The EWMA of the predicted values is a moving centre line, reflecting current patient case mix at a particular hospital. Thresholds around this moving centre line provide a scale by which to assess the importance of trends in the EWMA of the observed values. RESULTS The RA-EWMA chart can be designed to have equivalent performance, in terms of average run lengths, as variable life adjusted display chart. The advantages of the RA-EWMA are that it communicates information about the current level of an indicator in a direct and understandable way, and it explicitly displays information about the current patient case mix. Also, because it is not reset, the RA-EWMA is a more natural chart to use in health, where it is exceedingly rare to stop or dramatically and abruptly alter a process of care. CONCLUSION The RA-EWMA chart is a direct and intuitive way to display information about an indicator while accounting for differences in case mix.

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“…The scheme can detect changes in the process that were small enough to escape detection by the Shewhart chart and large enough to escape detection by the EWMA chart. The procedure was suggested by [1] and the need for combined applications of the two schemes was stressed by [3]. In simulations, [4] showed that a CS-EWMA control chart could detect shifts in a process faster than runs rules based Shewhart chart.…”

Section: Introductionmentioning

confidence: 99%

An Improved Combined Shewhart-EWMA Chart based on Double Median Ranked Set Sampling

Abujiya¹,

Lee²,

Riaz³

2014

JCSCM

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This study analyzes the performance of a combined Shewhart-EWMA control chart based on double median ranked set sampling (DMRSS), for efficient monitoring of changes in process mean level. The numerical performances of the proposed scheme were evaluated in terms of the average run length (ARL), standard deviation of run length, the average ratio ARL and average extra quadratic loss. Results show that the use of a well-structured sampling method on the combined scheme has greatly enhanced the performance of the scheme in detecting all kinds of shifts in a process. We present a comparison of the proposed scheme with some location charts for monitoring changes in a process. Practical application of the proposed scheme is also demonstrated using real industrial data.

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[Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements]: Discussion

Cited by 14 publications

References 0 publications

Comparison of Critical Care Occupancy and Outcomes of Critically Ill Patients during the 2020 COVID-19 Winter Surge and 2009 H1N1 Influenza Pandemic in Australia

Comparison of Critical Care Occupancy and Outcomes of Critically Ill Patients during the 2020 COVID-19 Winter Surge and 2009 H1N1 Influenza Pandemic in Australia

Exponentially weighted moving average charts to compare observed and expected values for monitoring risk-adjusted hospital indicators

An Improved Combined Shewhart-EWMA Chart based on Double Median Ranked Set Sampling

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