The design of various statistical methods formonitoring rare health events shows significance of the issue in healthsectors. Rare health events, as attribute quality characteristics cannot bemonitored by ordinary Shewhart np charts since overdispersion occurs. A goodapproach to this problem is the use of control charts based on zero inflationin a binomial (ZIB) distribution. In this distribution, it is assumed thatrandom shocks occur with some probability, and upon the occurrence of suchrandom shocks, health event failures can be found, such that the number offailures in each sampling subgroup follows a binomial distribution. This studydevelops a truncated ZIB control chart applying probability limits in Shewhartbased control limits for monitoring ZIB distributed observations. As the mostwidespread criteria, Average Run Length approach is used to evaluate theperformance of this chart. The use of truncated zero inflation in a binomial(TZIB) control chart is also investigated by a real case study, using thenumber of patients who undergone Tuberculosis treatment and later resulted toDrug Resistant Tuberculosis (DRTB) in General Hospital, Igarra, Akoko-Edo LocalGovernment of Edo State. Results are compared with the traditional number ofproportion defective (np) chart.
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