830 infection control & hospital epidemiology july 2018, vol. 39, no. 7


figure 2. Development results (January–March 2015). Shown are both the adjudicated classifications by ventilator-associated event (VAE) type, as well as a summary 2×2 table with the calculated sensitivities, specificities, and positive predictive values for both manual surveillance (MS) and automated surveillance (AS).


figure 3. Validation results (January–March 2016). Shown are both the adjudicated classifications by ventilator-associated event (VAE) type, as well as a summary 2×2 table with the calculated sensitivities, specificities, and positive predictive values for both manual surveillance (MS) and automated surveillance (AS).


An example of automated surveillance detection of an IVACcase is provided in Figure 4.


discussion


We found that completely automated surveillance, relying on physiologic data streamed live frombedsidemonitors, combined with clinical data available in the EHR, was superior to manual surveillance conducted by experienced IC practitioners.With the exception of a technical data lapse during the validation period when physiologic data were not available, automated surveil- lance performed with perfect sensitivity and specificity. Manual detection was subject to human error, including missed cases, misclassifications of detected cases, and false detections. The use of data visualization techniques to summarize results of the


automated process made interpreting and verifying findings during automated surveillance straightforward, which increased the efficiency of the surveillance process. Our findings are consistent with those of others who have reported on efforts to transition from manual to partially automated VAE surveillance, with some important differences. Stevens et al6 conducted a retrospective review of all admis- sions to any of 9 ICUs at a single hospital over a 6-year period. The algorithm extracted all data elements from the EHR, but the data used to identify mechanically ventilated patients as well as ventilator settings were based on manual entry to the EHR by respiratory therapists, a process that introduces the possibility of data entry error. Notably, “misapplication” refers to incorrect application of VAE definitions, rather than errors arising from missing data. The algorithm was sensitive


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