DCASIP faculty Drs. Art Baker and Dev Anderson worked with Healthcare Systems Engineering Institute, in Boston, MA to discuss the use of optimised dual statistical process control charts for early detection of SSI outbreaks in BMJ Quality & Safety.
Surgical site infections (SSI) are common healthcare-associated infections resulting in substantial morbidity, mortality and hospital costs. However, no standard algorithm for SSI surveillance or outbreak detection exists, and traditional surveillance techniques may fail to provide timely identification of important SSI rate increases. We previously showed that standard Shewhart and exponentially weighted moving average statistical process control (SPC) charts have potential to provide early detection of SSI outbreaks. We then performed a large-scale empirical optimisation study and determined that simultaneous use of two moving average (MA) SPC charts in this application was most effective in identifying clinically important increases in SSI rates, or SSI clusters, that occurred in our network of community hospitals. The objective of the current analysis was to evaluate the performance of this optimised combination of control charts when applied to known SSI outbreaks.
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