Abstract
BackgroundSurveillance 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).AimThe 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.MethodsWe analysed the data of 77 hospital-wide PPS, performed over a 2-year period (2013 and 2014) and including 25,056 patients.ResultsSix 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.ConclusionPerforming computer-assisted, high frequency hospital-wide PPS, is a feasible method that will detect even subtle changes in HAI prevalence over time.
Highlights
Many hospitals rely for their surveillance of hospital-acquired infections (HAI) on a standardised hospital-wide point prevalence survey (PPS) to obtain information about the prevalence and types of HAI in their hospital
The patients who were excluded consisted of three groups: (i) patients who did not meet the clinical inclusion criteria, for example the haemodialysis patients, (ii) patients whose admission period did not include a Thursday (PPS day), i.e. admitted after a Thursday and discharged before the following Thursday, and (iii) patients for whom Thursday was the admission date and who were discharged before the Thursday
Review by the infection control professional (ICP) of these 15,051 Nii scores resulted in the ascertainment of 2,810 HAI, i.e. 112 HAI per 1,000 patients included in the surveys
Summary
Many hospitals rely for their surveillance of hospital-acquired infections (HAI) on a standardised hospital-wide point prevalence survey (PPS) to obtain information about the prevalence and types of HAI in their hospital. The number of patients per department and per medical discipline included in each PPS is commonly too low to detect meaningful trends with any statistical power. To address these issues, one could perform multiple serial PPS at a much higher frequency, e.g. every month or even every week. 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. Conclusion: Performing computerassisted, high frequency hospital-wide PPS, is a feasible method that will detect even subtle changes in HAI prevalence over time
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