1005Empirical Performance of Statistical Process Control Methods for Regional Hospital-Acquired Infection Surveillance: A 10-Year Multi-State Study

Background. Use of statistical process control (SPC) in healthcare is increasing but remains less common than in other industries. Healthcare-associated infections (HAIs) are important applications that can benefit from SPC methods, including use within existing surveillance programs to trigger investigation and intervention. The empirical value of SPC, however, typically is anecdotal and remains unclear to many practitioners. Methods. We retrospectively applied Shewhart and EWMA SPC charts to 10 years (2003 to 2013) of de-identified surgical site infection (SSI) data, including 8 known SSI outbreaks, from the Duke Infection Control Outreach Network of 40 community hospitals. For both methods, we computed the number of outbreaks detected, months of earlier detection vs traditional surveillance, and total signals produced (TS) over the entire study period as a workload measure. To distinguish between minor unsustained vs major sustained HAI rate increases, we additionally calculated the number of months with signals during the year prior (PS) to each outbreak, monthly consecutive signals (CS) before each outbreak, and signals during each outbreak period (DS). Results. All known outbreaks were detected by all charts 0 to 12 months earlier than known start dates, on average by 5.8 (Shewhart) and 6.8 (EWMA) months (table). 62.5% of these earlier detections included more than one signal. The total number of signals over the study period (outbreaks, uncertain, or false alarms) averaged 5.5 (Shewhart) and 16.5 (EWMA) per outbreak hospital.