Validation of an automated surveillance approach for XXXX : a multicenter study.

@entity1 @entity281 @entity693
OBJECTIVE Manual surveillance of healthcare-associated @entity281 is cumbersome and vulnerable to subjective interpretation. Automated systems are under development to improve efficiency and reliability of surveillance, for example by selecting high-risk @entity1 requiring manual chart review. In this study, we aimed to validate a previously developed multivariable prediction modeling approach for detecting @entity693 ( @entity693 ) in neurosurgical @entity1 and to assess its merits compared to conventional methods of automated surveillance. METHODS Prospective cohort study in 3 hospitals assessing the accuracy and efficiency of 2 automated surveillance methods for detecting @entity693 , the multivariable prediction model and a classification algorithm, using manual chart review as the reference standard. All 3 methods of surveillance were performed independently. @entity1 receiving cerebrospinal fluid drains were included (2012-2013), except @entity1 , and @entity1 deceased within 24 hours or with pre-existing @entity693 . Data required by automated surveillance methods were extracted from routine care clinical data warehouses. RESULTS In total, @entity693 occurred in 37 of 366 external cerebrospinal fluid drainage episodes (12.3/1000 drain days at risk). The multivariable prediction model had good discriminatory power (area under the ROC curve 0.91-1.00 by hospital), had adequate overall calibration, and could identify high-risk @entity1 requiring manual confirmation with 97.3% sensitivity and 52.2% positive predictive value, decreasing the workload for manual surveillance by 81%. The multivariable approach was more efficient than classification algorithms in 2 of 3 hospitals. CONCLUSIONS Automated surveillance of @entity693 using a multivariable prediction model in multiple hospitals considerably reduced the burden for manual chart review at near-perfect sensitivity. Infect Control Hosp Epidemiol 2015;36(1): 65-75.
