Objective: This research is designed to examine the impact of varying patient population distributions on the in-control performance of the risk-adjusted Bernoulli CUSUM chart.
Design: The in-control performance of the chart is compared based on sampling the Parsonnet scores with replacement from five realistic subsets of a given distribution.
Settings: Five patient mixes with different Parsonnet score distributions are created from a real patient population.
Main outcome measures: The outcome measures for this research are the in-control average run lengths (ARLs) given varying patient populations.
Results: Our simulation results show that the in-control ARLs of the risk-adjusted Bernoulli CUSUM chart with fixed control limits and a given risk-adjustment equation vary significantly for different patient population distributions, and the in-control ARLs decrease as the mean of the Parsonnet scores increases.
Conclusions: The simulation results imply that the control limits should vary based on the particular patient population of interest in order to control the in-control performance of the risk-adjusted Bernoulli CUSUM method.
Keywords: Parsonnet score; average run length (ARL); heterogeneous population distributions; in-control performance; risk-adjusted CUSUM; statistical process control.
© The Author 2014. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.