Literature DB >> 19247982

Risk-adjusted monitoring of survival times.

Landon H Sego1, Marion R Reynolds, William H Woodall.   

Abstract

We consider the monitoring of surgical outcomes, where each patient has a different risk of post-operative mortality due to risk factors that exist prior to the surgery. We propose a risk-adjusted (RA) survival time CUSUM chart (RAST CUSUM) for monitoring a continuous, time-to-event variable that may be right-censored. Risk adjustment is accomplished using accelerated failure time regression models. We compare the average run length performance of the RAST CUSUM chart with the RA Bernoulli CUSUM chart using data from cardiac surgeries to motivate the details of the comparison. The comparisons show that the RAST CUSUM chart is more efficient at detecting a sudden increase in the odds of mortality than the RA Bernoulli CUSUM chart, especially when the fraction of censored observations is relatively low or when a small increase in the odds of mortality occurs. We also discuss the impact of the amount of training data used to estimate chart parameters as well as the implementation of the RAST CUSUM chart during prospective monitoring. John Wiley & Sons, Ltd

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Year:  2009        PMID: 19247982     DOI: 10.1002/sim.3546

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  7 in total

1.  Monitoring the one year postoperative infection rate after primary total hip replacement.

Authors:  David J Biau; Philippe Leclerc; Simon Marmor; Valerie Zeller; Wilfrid Graff; Luc Lhotellier; Philippe Leonard; Patrick Mamoudy
Journal:  Int Orthop       Date:  2011-12-30       Impact factor: 3.075

2.  An omnibus CUSUM chart for monitoring time to event data.

Authors:  Ioannis Phinikettos; Axel Gandy
Journal:  Lifetime Data Anal       Date:  2013-09-24       Impact factor: 1.588

3.  Tests of calibration and goodness-of-fit in the survival setting.

Authors:  Olga V Demler; Nina P Paynter; Nancy R Cook
Journal:  Stat Med       Date:  2015-02-11       Impact factor: 2.373

4.  Change point estimation in monitoring survival time.

Authors:  Hassan Assareh; Kerrie Mengersen
Journal:  PLoS One       Date:  2012-03-16       Impact factor: 3.240

5.  The STRAND Chart: A survival time control chart.

Authors:  Olivia Aj Grigg
Journal:  Stat Med       Date:  2018-12-26       Impact factor: 2.373

6.  Modeling the patient mix for risk-adjusted CUSUM charts.

Authors:  Philipp Wittenberg
Journal:  Stat Methods Med Res       Date:  2022-03-10       Impact factor: 2.494

7.  Risk-adjusted monitoring of surgical performance.

Authors:  Jianbo Li; Jiancheng Jiang; Xuejun Jiang; Lin Liu
Journal:  PLoS One       Date:  2018-08-08       Impact factor: 3.240

  7 in total

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