TY - CONF
T1 - Control charts for health care monitoring under intermittent out-of-control behavior
AU - Albers, Willem
N1 - Conference code: 58
PY - 2011
Y1 - 2011
N2 - Health care monitoring typically concerns attribute data with very low failure rates. Efficient control charts then signal if the waiting time till r (e.g. r≤5) failures is too small. An interesting alternative is the MAX-chart, which signals if all the associated r waiting times for a single failure are sufficiently small. In comparing these choices, the usual change point set-up has been used, in which going Out-of-Control (OoC) means that the failure rate suddenly jumps up and then stays at this higher level. However, another situation of interest is intermittent OoC behavior. In industrial settings, an OoC process can be adjusted to return to In-Control (IC), but with health care monitoring this usually is no option and stretches of OoC and IC behavior may alternate. Comparison of such intermittent alternatives to the change point situation shows that the former can be characterized as tail alternatives, in the sense that the difference w.r.t. the IC-distribution becomes more concentrated in the lower tail. This suggests to generalize the MAX-chart as follows: now signal if all but 1 (or 2) out of r individual waiting times are too small. A numerical study shows that this approach indeed works well.
AB - Health care monitoring typically concerns attribute data with very low failure rates. Efficient control charts then signal if the waiting time till r (e.g. r≤5) failures is too small. An interesting alternative is the MAX-chart, which signals if all the associated r waiting times for a single failure are sufficiently small. In comparing these choices, the usual change point set-up has been used, in which going Out-of-Control (OoC) means that the failure rate suddenly jumps up and then stays at this higher level. However, another situation of interest is intermittent OoC behavior. In industrial settings, an OoC process can be adjusted to return to In-Control (IC), but with health care monitoring this usually is no option and stretches of OoC and IC behavior may alternate. Comparison of such intermittent alternatives to the change point situation shows that the former can be characterized as tail alternatives, in the sense that the difference w.r.t. the IC-distribution becomes more concentrated in the lower tail. This suggests to generalize the MAX-chart as follows: now signal if all but 1 (or 2) out of r individual waiting times are too small. A numerical study shows that this approach indeed works well.
KW - Average run length
KW - MSC-62P10
KW - Tail alternatives
KW - Statistical Process Control
KW - High quality processes
M3 - Paper
T2 - 58th World Statistics Congress, ISI 2011
Y2 - 21 August 2011 through 26 August 2011
ER -