Development and validation of an automated ventilator‐associated event electronic surveillance system: A report of a successful implementation

Background: Surveillance is an important tool for infection control; however, this task can often be time‐consuming and take away from infection prevention activities. With the increasing availability of comprehensive electronic health records, there is an opportunity to automate these surveillance activities. The objective of this article is to describe the implementation of an electronic algorithm for ventilator‐associated events (VAEs) at a large academic medical center Methods: This article reports on a 6‐month manual validation of a dashboard for VAEs. We developed a computerized algorithm for automatically detecting VAEs and compared the output of this algorithm to the traditional, manual method of VAE surveillance. Results: Manual surveillance by the infection preventionists identified 13 possible and 11 probable ventilator‐associated pneumonias (VAPs), and the VAE dashboard identified 16 possible and 13 probable VAPs. The dashboard had 100% sensitivity and 100% accuracy when compared with manual surveillance for possible and probable VAP. We report on the successfully implemented VAE dashboard. Workflow of the infection preventionists was simplified after implementation of the dashboard with subjective time‐savings reported. Conclusions: Implementing a computerized dashboard for VAE surveillance at a medical center with a comprehensive electronic health record is feasible; however, this required significant initial and ongoing work on the part of data analysts and infection preventionists.