A Method for Detecting Runs of Good and Bad Clinical Outcomes on Variable Life-Adjusted Display (VLAD) Charts

Sherlaw-Johnson, C

doi:10.1007/s10729-005-5217-2

Cited by 50 publications

(43 citation statements)

References 16 publications

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“…A signaling rule provides an objective and quantitative way for assessing the plotted points and determining appropriate times for taking action. Sherlaw-Johnson (2005) mapped the control limits of the risk-adjusted cumulative sum (CUSUM) chart onto the variable life-adjusted display but the resulting signaling rule is complicated because the control limits change with inclusion of data from every new surgical operation.…”

Section: Introductionmentioning

confidence: 99%

“…Their approach uses a risk-adjusted likelihood ratio statistic as the penalty-reward score. The riskadjusted CUSUM chart and variable life-adjusted display are developed using two different approaches and are viewed as two different charts (Spiegelhalter et al 2003;Rogers et al 2004;Sherlaw-Johnson 2005;Woodall 2006). Gan, Lin, and Loke (2012) showed that the risk-adjusted CUSUM chart (Steiner, Cook, and Farewell 1999) and the CUSUM chart constructed using the likelihood ratio statistic based on the variable lifeadjusted display's monitoring statistic (difference between expected and actual mortality) are in fact the same because the two monitoring statistics contain the same information.…”

Section: Introductionmentioning

confidence: 99%

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Risk-Adjusted Cumulative Sum Charting Procedure Based on Multiresponses

Tang¹,

Gan²,

Zhang³

2015

Journal of the American Statistical Association

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The cumulative sum charting procedure is traditionally used in the manufacturing industry for monitoring the quality of products. Recently, it has been extended to monitoring surgical outcomes. Unlike a manufacturing process where the raw material is usually reasonably homogeneous, patients' risks of surgical failure are usually different. It has been proposed in the literature that the binary outcomes from a surgical procedure be adjusted using the preoperative risk based on a likelihood-ratio scoring method. Such a crude classification of surgical outcome is naive. It is unreasonable to regard a patient who has a full recovery, the same quality outcome as another patient who survived but remained bed-ridden for life. For a patient who survives an operation, there can be many different grades of recovery. Thus, it makes sense to consider a risk-adjusted cumulative sum charting procedure based on more than two outcomes to better monitor surgical performance. In this article, we develop such a chart and study its performance.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Risk-Adjusted Cumulative Sum Charting Procedure Based on Multiresponses

Tang¹,

Gan²,

Zhang³

2015

Journal of the American Statistical Association

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“…It has been pointed out that the CUSUM chart is not, by itself, very revealing and a combined chart has been proposed [18]. We have adopted this approach of combining the two charts but in a slightly simpler manner; CUSUM signals are indicated by the presence of a prominent arrow.…”

Section: Discussionmentioning

confidence: 99%

An Application of Outcomes Monitoring for Coronary Artery Bypass Surgery 2005–2008 at TPCH

Morton

Smith

Mullany

et al. 2011

Heart, Lung and Circulation

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“…A solution to this problem is a surveillance scheme that combines the VLAD and RA-CUSUM 6. The VLAD plot indicates the trends, and the RA-CUSUM2 signals that the trends are potentially important.…”

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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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A Method for Detecting Runs of Good and Bad Clinical Outcomes on Variable Life-Adjusted Display (VLAD) Charts

Cited by 50 publications

References 16 publications

Risk-Adjusted Cumulative Sum Charting Procedure Based on Multiresponses

Risk-Adjusted Cumulative Sum Charting Procedure Based on Multiresponses

An Application of Outcomes Monitoring for Coronary Artery Bypass Surgery 2005–2008 at TPCH

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

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