The Multivariate EWMA Model and Monitoring Bio Surveillance

In this study, we examine a common problem is bio surveillance in health care. Bio surveillance is the process of monitoring health data to assess changes in the likelihood of disease incidence. Based on an illustration, we suggest that multivariate exponential moving-average (MEWMA) control charts are suitable in most cases where detection and Inspection of several or more variables over a lengthy period of testing provide for the best analysis of data leading to pre-¬diagnostic and diagnostic therapy. Though these methods came from the control of quality and continuous improvement in lean manufacturing and service operations, these methods have useful if not vital application in the analysis of health care data. The indications from this study corroborate earlier findings by others that MEWMA methods fit the diagnostic activity under study. Keywords: Multivariate Quality Control (MPC), Mult ivariate Exponentially Weighted Moving Average (MEWMA), Bio Surveillance, Correlation among variables, Serial Correlation.