Abstract
Overdispersion is a phenomenon that generally occurs in the analysis of large sample sizes. In discrete data analysis, it refers to the presence of a variation higher than that implied by a reference Binomial or Poisson distributions. The proportion of nonconforming units in clinical laboratories presents high variability and, generally, overdispersion. Therefore, it is required to analyze the most appropriate control charts that overcome the limitations of traditional control charts to deal with overdispersed data. This paper performs an analysis of monitoring overdispersed process in clinical laboratories using control charts. The methodology consists of four steps: (i) Determination of the interest variable, (ii) Diagnosis of data overdispersion, (iii) Elaboration of control charts, and (iv) Analysis of results. The results show that the methodology can quantitatively determine the degree of data overdispersion and select the most appropriate control chart for monitoring the process.
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