Internal and External Validation of a Computer-Assisted Surveillance System for Hospital-Acquired Infections in a 754-Bed General Hospital in the Netherlands

Abstract

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.

Computer-assisted, high-frequency, hospital-wide point prevalence surveys of hospital-acquired infections in a tertiary care hospital, the Netherlands, 2013 to 2014

“…PPS are generally believed to be more cost-effective than incidence surveys, and this is supported by our experience in this 1,320-bed university hospital where weekly hospital-wide CAPPS required the dedication of approximately one full-time equivalent ICP [3-5]. Using this algorithm-based method, 71% of the patients were automatically excluded from review by the ICP and marked negative.…”

“…An in-house developed algorithm-driven and previously validated software programme was used to perform the CAPPS [3-5]. A full description of this method is available in the Supplement.…”

“…In our university hospital, we validated an algorithm (nosocomial infection index (Nii)) and implemented software to assist our infection control team to perform hospital-wide PPS more efficiently, as we previously reported [3,4]. The method was subsequently validated in a general hospital setting [5]. In the present manuscript, we primarily aimed to show how the results of frequently performed, hospital-wide computer-assisted PPS (CAPPS) could be converted into information about trends by type of HAI and by ward or medical specialty level, and how the frequency of measurements would affect the trend analyses.…”

Epidemiology, antimicrobial resistance, and incremental medical costs of hospital-acquired infections in the Intensive Care Unit: 2-year experience from Serbia

“…Risk factors confirmed in other studies (such as prior room occupants) [34], as well as other variables necessary for an in-depth analysis of HAI occurrence were not available for analysis. The same limitation applies to the calculation of medical costs (both direct and indirect), which would be more comprehensive if a prospective study was conducted, possibly through use of automated systems for HAI surveillance [35,36].…”

Validation of a semi-automated surveillance system for surgical site infections: Improving exhaustiveness, representativeness, and efficiency

“…This latter model has been increasingly tested throughout the world (Chalfine et al, 2006;Hu et al, 2015;Streefkerk et al, 2016;Trick et al, 2004;Woeltje, 2013). It provides objective and consistent definitions across time and institutions for benchmarking purposes, expands current surveillance to include all surgeries, is less time-consuming, and is less affected by human error (van Mourik, 2018;Streefkerk et al, 2016Streefkerk et al, , 2014Trick et al, 2004). However, it requires validation in each setting, as it needs to be customized to maximally support hospital surveillance efforts (van Mourik et al, 2015).…”