Binary Cumulative Sums and Moving Averages in Nosocomial Infection Cluster Detection

摘要

Clusters of nosocomial infection often occur undetected, at substantial cost to the medical system andindividual patients. We evaluated binary cumulative sum (CUSUM) and moving average (MA) controlcharts for automated detection of nosocomial clusters. We selected two outbreaks with genotyped strainsand used resistance as inputs to the control charts. We identified design parameters for the CUSUM andMA (window size, k, a, b, p0, p1) that detected both outbreaks, then calculated an associated positive pre-dictive value (PPV) and time until detection (TUD) for sensitive charts. For CUSUM, optimal performance(high PPV, low TUD, fully sensitive) was for 0.1 <α<0.25 and 0.2 <β <0.25, with p0= 0.05, with a meanTUD of 20 (range 8–43) isolates. Mean PPV was 96.5% (relaxed criteria) to 82.6% (strict criteria). MAshad a mean PPV of 88.5% (relaxed criteria) to 46.1% (strict criteria). CUSUM and MA may be useful tech-niques for automated surveillance of resistant infections