A Comparative Study of Control Charts for Monitoring Rare Events in Health Systems Using Monte Carlo Simulation Open Access
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Rare events in healthcare can pose a challenging issue for quality practitioners, particularly in deciding how to monitor them with control charts. There are many examples of rare events data in healthcare settings including medication errors, patient falls, birth traumas, surgical site infections and ventilator-associated events. So, it is necessary to find better ways to monitor rare events in health systems.Some have argued against utilizing control charts with healthcare rare events data because assignable causes are present for each error and each incident should be investigated. However, although it is important to investigate individual adverse events, it is equally important to monitor and study such events over time as this can often lead to significant improvements in quality. Control charts are graphical time series that help us to study processes over time for improving quality of care and reducing adverse events.The purpose of this praxis is to conduct a comparative study of control charts that have been proposed in literature for monitoring rare events and to determine which control charts perform better using Monte Carlo simulation. Recommendations on which control charts to use for monitoring rare events in health systems will be provided at the conclusion of this study. Also, real healthcare data will be used to demonstrate the application of this work.