Background: Surveillance of healthcare-associated infections (HAI) is the basis of each infection control programme and, in case of acute care hospitals, should ideally include all hospital wards, medical specialties as well as all types of HAI. Traditional surveillance is labour intensive and electronically assisted surveillance systems (EASS) hold the promise to increase efficiency. Objectives: To give insight in the performance characteristics of different approaches to EASS and the quality of the studies designed to evaluate them. Methods: In this systematic review, online databases were searched and studies that compared an EASS with a traditional surveillance method were included. Two different indicators were extracted from each study, one regarding the quality of design (including reporting efficiency) and one based on the performance (e.g. specificity and sensitivity) of the EASS presented. Results: A total of 78 studies were included. The majority of EASS (n = 72) consisted of an algorithm-based selection step followed by confirmatory assessment. The algorithms used different sets of variables. Only a minority (n = 7) of EASS were hospital-wide and designed to detect all types of HAI. Sensitivity of EASS was generally high (> 0.8), but specificity varied (0.37-1). Less than 20% (n = 14) of the studies presented data on the efficiency gains achieved. Conclusions: Electronically assisted surveillance of HAI has yet to reach a mature stage and to be used routinely in healthcare settings. We recommend that future studies on the development and implementation of EASS of HAI focus on thorough validation, reproducibility, standardised datasets and detailed information on efficiency.

OBJECTIVE To evaluate a computer-assisted point-prevalence survey (CAPPS) for hospital-acquired infections (HAIs). DESIGN Validation cohort. SETTING A 754-bed teaching hospital in the Netherlands. METHODS For the internal validation of a CAPPS for HAIs, 2,526 patients were included. All patient records were retrospectively reviewed in depth by 2 infection control practitioners (ICPs) to determine which patients had suffered an HAI. Preventie van Ziekenhuisinfecties door Surveillance (PREZIES) criteria were used. Following this internal validation, 13 consecutive CAPPS were performed in a prospective study from January to March 2013 to determine weekly, monthly, and quarterly HAI point prevalence. Finally, a CAPPS was externally validated by PREZIES (Rijksinstituut voor Volksgezondheid en Milieu [RIVM], Bilthoven, Netherlands). In all evaluations, discrepancies were resolved by consensus. RESULTS In our series of CAPPS, 83% of the patients were automatically excluded from detailed review by the ICP. The sensitivity of the method was 91%. The time spent per hospital-wide CAPPS was ~3 hours. External validation showed a negative predictive value of 99.1% for CAPPS. CONCLUSIONS CAPPS proved to be a sensitive, accurate, and efficient method to determine serial weekly point-prevalence HAI rates in our hospital. Infect Control Hosp Epidemiol 2016;1-6.

Background Surveillance of hospital-acquired infections (HAI) often relies on point prevalence surveys (PPS) to detect major deviations in the occurrence of HAI, supplemented with incidence measurements when more detailed information is needed. In a 1,320-bed university medical centre in the Netherlands, we evaluated an electronically assisted surveillance system based on frequently performed computer-assisted PPS (CAPPS). Aim The primary goals were to evaluate the performance of this method to detect trends and to determine how adjustments in the frequency with which the CAPPS are performed would affect this performance. A secondary goal was to evaluate the performance of the algorithm (nosocomial infection index (Nii)) used. Methods We analysed the data of 77 hospital-wide PPS, performed over a 2-year period (2013 and 2014) and including 25,056 patients. Results Six trends with statistical significance were detected. The probability to detect such trends rapidly decreased when PPS are performed at a lower frequency. The Nii and its dynamics strongly correlated with the presence of HAI. Conclusion Performing computer-assisted, high frequency hospital-wide PPS, is a feasible method that will detect even subtle changes in HAI prevalence over time.