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Dynamic probability control limits for risk‐adjusted CUSUM charts based on multiresponses
Authors:Xiang Zhang  Justin B Loda  William H Woodall
Institution:1. Pfizer Worldwide Research and Development, Pharm Sci and PGS Statistics, Groton, CT, U.S.A.;2. Department of Statistics, Virginia Tech, Blacksburg, VA, U.S.A.
Abstract:For a patient who has survived a surgery, there could be several levels of recovery. Thus, it is reasonable to consider more than two outcomes when monitoring surgical outcome quality. The risk‐adjusted cumulative sum (CUSUM) chart based on multiresponses has been developed for monitoring a surgical process with three or more outcomes. However, there is a significant effect of varying risk distributions on the in‐control performance of the chart when constant control limits are applied. To overcome this disadvantage, we apply the dynamic probability control limits to the risk‐adjusted CUSUM charts for multiresponses. The simulation results demonstrate that the in‐control performance of the charts with dynamic probability control limits can be controlled for different patient populations because these limits are determined for each specific sequence of patients. Thus, the use of dynamic probability control limits for risk‐adjusted CUSUM charts based on multiresponses allows each chart to be designed for the corresponding patient sequence of a surgeon or a hospital and therefore does not require estimating or monitoring the patients' risk distribution. Copyright © 2017 John Wiley & Sons, Ltd.
Keywords:average run length (ARL)  false alarm rate  proportional odds logistic regression  statistical process monitoring  surgical performance
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