A risk‐adjusted Sets method for monitoring adverse medical outcomes

Grigg, O. A.; Farewell, Vernon T.

doi:10.1002/sim.1763

Cited by 39 publications

(22 citation statements)

References 10 publications

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“…Fig. 5 illustrates a sets chart (grass plot), as proposed by Grigg and Farewell (2004), with values of n and T that are appropriate for the example 1 data. The chart simply plots the observation number against the cumulative size of the current set or blade.…”

Section: 1 Examplementioning

confidence: 99%

An Overview of Risk-Adjusted Charts

Grigg

Farewell

2004

Journal of the Royal Statistical Society Series A: Statistics in Society

108

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The paper provides an overview of risk-adjusted charts, with examples based on two data sets: the first consisting of outcomes following cardiac surgery and patient factors contributing to the Parsonnet score; the second being age-sex-adjusted death-rates per year under a single general practitioner. Charts presented include the cumulative sum (CUSUM), resetting sequential probability ratio test, the sets method and Shewhart chart. Comparisons between the charts are made. Estimation of the process parameter and two-sided charts are also discussed. The CUSUM is found to be the least efficient, under the average run length (ARL) criterion, of the resetting sequential probability ratio test class of charts, but the ARL criterion is thought not to be sensible for comparisons within that class. An empirical comparison of the sets method and CUSUM, for binary data, shows that the sets method is more efficient when the in-control ARL is small and more efficient for a slightly larger range of in-control ARLs when the change in parameter being tested for is larger. The Shewart "p"-chart is found to be less efficient than the CUSUM even when the change in parameter being tested for is large. Copyright 2004 Royal Statistical Society.

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Section: 1 Examplementioning

confidence: 99%

An Overview of Risk-Adjusted Charts

Grigg

Farewell

2004

Journal of the Royal Statistical Society Series A: Statistics in Society

108

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“…These charts provide an earlier alert when a process is going to be out-of-control, so that an action can be taken to bring back it to the in-control state. Although such charts originated from industry applications, their use has been extended to monitoring of environmental and health risk; see Grigg and Farewell [11], Woodall [35], Morrison [26], and Manly [24].…”

Section: Introductionmentioning

confidence: 99%

Monitoring Environmental Risk by a Methodology Based on Control Charts

Saulo

Leiva

Ruggeri

2015

Springer Proceedings in Mathematics &Amp; Statistics

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“…Statistical methods for the surveillance of health care outcomes have recently gained momentum. In particular, risk‐adjusted cumulative sum (RACUSUM) charts have been developed for the surveillance of binary outcomes such as the 30‐day mortality rates of patients undergoing heart surgery (see, for instance, Steiner et al, ; Frisen, ; Grigg & Farewell, ; Grigg & Spiegelhalter, ; Gombay, Hussein, & Steiner, ).…”

Section: Introductionmentioning

confidence: 99%

Flexible risk‐adjusted surveillance procedures for autocorrelated binary series

2015

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Risk‐adjusted cumulative sum (RACUSUM) charts are popular for the surveillance of binary health care outcomes such as 30‐day mortality rates following cardiac surgery. RACUSUM charts are built on the assumptions that the binary outcomes are independent and the baseline rates are known constants. However, these two assumptions are often violated, thus undermining the validity of the surveillance procedure. In this paper, the authors propose risk‐adjusted surveillance procedures using a binary logistic regression model which allows italicARfalse(pfalse)‐type autocorrelations among the binary outcomes. Two versions are presented: one with known, the other with estimated baseline parameters. The authors use Monte Carlo experiments to evaluate the power and the probability of false alarm (Type I error) of the surveillance procedures. Data on 30‐day mortality rates following cardiac surgery are used for illustration. The Canadian Journal of Statistics 43: 403–419; 2015 © 2015 Statistical Society of Canada

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A risk‐adjusted Sets method for monitoring adverse medical outcomes

Cited by 39 publications

References 10 publications

An Overview of Risk-Adjusted Charts

An Overview of Risk-Adjusted Charts

Monitoring Environmental Risk by a Methodology Based on Control Charts

Flexible risk‐adjusted surveillance procedures for autocorrelated binary series

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