ViRTUE, a virtual reality (VR) hand hygiene trainer, offers users the option of visualizing pathogen transfers during virtual patient care either in “real-time” or at the end of a level as a “summary” visualization. In this study, we aimed to evaluate the effect of different timings of pathogen visualization (“real-time” vs “summary”) on in-trainer performance and user’s immersion.

The study included first-year medical students undergoing hand hygiene training with ViRTUE, randomized to one of three visualization set-ups: set-up 1 (“on-off-off”, with “real-time” visualization at the first level only, and “summary” visualization at level 2 and 3), set-up 2 (“off-on-off”), and set-up 3 (“off-off-off”). In-trainer performance was defined by number of pathogen transmission events (=contaminations) in level 3. The virtual experience of user’s (among others: immersion) was assessed with a questionnaire.

173 medical students participated in the study, with 58, 54, and 61 assigned to set-up 1, set-up 2, and set-up 3, respectively. Users assigned to set-up 3 with “summary” visualization at all levels, performed best with 1.02 (standard deviation (SD) +/- 1.86) contaminations, compared to 2.34 (SD +/- 3.09) and 2.07 (SD +/- 2.52) contaminations of users assigned to the other set-ups. “Summary” visualization at all levels also resulted in higher immersion of users.

“Real-time” visualization of pathogen transmission during VR hand hygiene training with ViRTUE may negatively affect in-trainer performance and user immersion. This emphasizes the importance of pilot testing the effect of VR-based trainings in order to understand their impact on users.

In 2017, a point-prevalence survey was conducted with 12,931 patients in 96 hospitals across Switzerland as part of the national strategy to prevent healthcare-associated infections (HAIs). We present novel statistical methods to assess incidence proportions of HAI and attributable length-of-stay (LOS) in point-prevalence surveys.

Follow-up data were collected for a subsample of patients and were used to impute follow-up data for all remaining patients. We used weights to correct length bias in logistic regression and multistate analyses. Methods were also tested in simulation studies.

The estimated incidence proportion of HAIs during hospital stay and not present at admission was 2.3% (95% confidence intervals [CI], 2.1–2.6), the most common type being lower respiratory tract infections (0.8%; 95% CI, 0.6–1.0). Incidence proportion was highest in patients with a rapidly fatal McCabe score (7.8%; 95% CI, 5.7–10.4). The attributable LOS for all HAI was 6.4 days (95% CI, 5.6–7.3) and highest for surgical site infections (7.1 days, 95% CI, 5.2–9.0). It was longest in the age group of 18–44 years (9.0 days; 95% CI, 5.4–12.6). Risk-factor analysis revealed that McCabe score had no effect on the discharge hazard after infection (hazard ratio [HR], 1.21; 95% CI, 0.89–1.63). Instead, it only influenced the infection hazard (HR, 1.84; 95% CI, 1.39–2.43) and the discharge hazard prior to infection (HR, 0.73; 95% CI, 0.66–0.82).

In point-prevalence surveys with limited follow-up data, imputation and weighting can be used to estimate incidence proportions and attributable LOS that would otherwise require complete follow-up data.

To assess the effect of peer-identified change agents (PICAs) compared to management-selected change agents (MSCAs) on hand hygiene behavior in acute care.

Randomized-controlled study.

Two internal medicine wards of a public, university-affiliated, tertiary-care hospital in Malaysia.

We randomly allocated 2 wards to hand hygiene promotion delivered either by PICAs (study arm 1) or by MSCAs (study arm 2). The primary outcome was hand hygiene compliance using direct observation by validated auditors. Secondary outcomes were hand hygiene knowledge and observations from ward tours.

Mean hand hygiene compliance in study arm 1 and study arm 2 improved from 48% (95% confidence interval [CI], 44%–53%) and 50% (95% CI, 44%–55%) in the preintervention period to 66% (63%–69%) and 65% (60%–69%) in the intervention period, respectively. We detected no statistically significant difference in hand hygiene improvement between the 2 study arms. Knowledge scores on hand hygiene in study arm 1 and study arm 2 improved from 60% and 63% to 98% and 93%, respectively. Staff in study arm 1 improved hand hygiene because they did not want to disappoint the efforts taken by the PICAs. Staff in study arm 2 felt pressured by the MSCAs to comply with hand hygiene to obtain good overall performance appraisals.

Although the attitude of PICAs and MSCAs in terms of leadership, mode of action and perception of their task by staff were very different, or even opposed, both PICAs and MSCAs effectively changed behavior of staff toward improved hand hygiene to comparable levels.

To assess the prevalence of healthcare-associated infections (HAIs) in mainland China.

Systematic review and meta-analysis.

Adults and children from secondary and tertiary acute-care hospitals in mainland China.

We searched PubMed, the China National Knowledge Infrastructure, and Wan Fang for multicenter point-prevalence surveys of acute-care hospitals in mainland China from January 2006 to August 2016. All reports related to HAI, using a point-prevalence methodology and published either in English or Chinese were eligible.

In total, 3,021 publications were identified; 115 were eligible for quality assessment and data abstraction. The weighted HAI prevalence (95% confidence interval [CI]) overall, in general hospitals, children’s hospitals, maternal and child health hospitals, and oncology hospitals were 3.12% (95% CI, 2.94%–3.29%), 3.02% (95% CI, 2.79%–3.26%), 4.43% (95% CI, 3.39%–5.47%), 1.88% (95% CI, 1.47%–2.29%), and 3.96% (95% CI, 3.12%–4.79%), respectively. In general hospitals, prevalence was highest in adult intensive care units (26.07%; 95% CI, 23.03%–29.12%), followed by surgery (3.26%; 95% CI, 2.96%–3.57%), and internal medicine (3.06%; 95% CI, 2.67%–3.46%). Overall, lower respiratory tract infection was the most frequent HAI (24,185, 47.28%), followed by urinary tract infection (5,773, 11.29%) and upper respiratory tract infection (5,194, 10.15%). Gram-negative bacilli were the most frequently isolated pathogens, and Pseudomonas aeruginosa (3,395, 14.91%), and Escherichia coli (2,918, 12.82%) were the most common single microorganisms.

This study is the largest systematic review on the prevalence of HAI in mainland China. These results provide a benchmark for future PPSs and a reference for infection prevention and control strategies in mainland China.

Infect Control Hosp Epidemiol 2018;39:701–709

To explore differences in the prevalence of healthcare-associated infections (HAIs) according to survey methodology.

Repeated point and period prevalence survey strategies.

University-affiliated primary and tertiary care center.

Analysis of data collected from 2006 to 2012 from annual HAI prevalence surveys using definitions proposed by the US Centers for Disease Control and Prevention. The study design allowed the analysis of the same data in the format of a point or a period prevalence survey.

Pooled point and period HAI prevalence was 7.46% and 9.84% (+32%), respectively. This additional 32% was mainly attributable to infections of the lower respiratory tract (2.42% vs 3.20% [+32%]) and the urinary tract (1.76% vs 2.62% [+49%]). Differences in surgical site infections (1.02% vs 1.20% [+19%]) and bloodstream infections (0.76% vs 0.86% [+13%]) were smaller. HAI prevalence for the point and period methodology in acute and long-term care were 7.47% versus 9.38 (+26%) and 8.37% versus 11.89% (+42%), respectively. Differences were stable over time. Focusing on the 4 major HAIs (respiratory tract, urinary tract, surgical site, and bloodstream infections) misses one-quarter of all HAIs.

More HAIs are identified by the period prevalence method, especially those of shorter duration (lower respiratory and urinary tract), which would make this method more suitable to be used in long-term care. Results of the 2 study methods cannot be benchmarked against each other.

Infect Control Hosp Epidemiol 2014;35(6):674–684

To monitor trends in central line-associated bloodstream infections and clinical sepsis (CLABICS) among neonates and to determine risk factors for infection, especially dwell time.

Prospective, single-center cohort study conducted from 2001 through 2008.

University-affiliated tertiary care center.

Individualized surveillance of catheter use and CLABICS episodes was conducted. Data were obtained via regular on-site visits made 3 times a week. Trends over time were estimated by Poisson regression, and risk factor analysis was conducted using a Cox proportional hazards model and logistic regression.

In all, 1,124 neonates were exposed to 2,210 central lines for a total of 12,746 catheter-days and 11,467 catheter-days at risk. The median duration of catheter use was 8 (interquartile range, 5–11) days for peripherally inserted central catheters (PICCs) and 4 (interquartile range, 2-6) days for umbilical catheters; 102 CLABICS episodes were detected. The median time to infection was 7 days. Incidence densities were 8.5 CLABICS episodes per 1,000 catheter-days at risk and 8.0 CLABICS episodes per 1,000 catheter-days. The highest rates were identified among neonates weighing 750 g or lower (14.9 CLABICS episodes per 1,000 catheter days at risk) and for PICCs (13.2 CLABICS episodes per 1,000 catheter days at risk). Catheter dwell time was associated with CLABICS for all umbilical catheters (odds ratio [OR], 1.2 per day of use [95% confidence interval {CI}, 1.1–1.3] P< .001) and for PICCs for up to 7 days (OR, 1.2 [95% CI, 1.1–1.4]; P = .041), but not thereafter (OR, 1.0 [95% CI, 0.9–1.1]; P = .90).

Catheter dwell time is a risk factor for CLABICS during the first 7 days, irrespective of catheter type. After 7 days, PICCs are less likely to become infected.

To describe a nosocomial norovirus outbreak, its management, and its financial impact on hospital resources.

A matched case-control study and microbiological investigation.

We compared 16 patients with norovirus infection with control-patients matched by age, gender, disease category, and length of stay. Bed occupancy-days during the peak incidence period of the outbreak were compared with the corresponding periods in 2001 and 2002. Expenses due to increased workload were calculated based on a measuring system that records time spent for nursing care per patient per day.

The attack rates were 13.9% among patients and 29.5% among healthcare workers. The median number of occupied beds was significantly lower due to bed closure during the peak incidence in 2003 (29) compared with the median number of occupied beds in 2001 and 2002 combined (42.5). Based on this difference and a daily charge of $562.50 per patient, we calculated a revenue loss of S37.968. Additional expenses totaled $10,300 for increased nursing care. Extra costs for microbiological diagnosis totaled $2,707. Lost productivity costs due to healthcare workers on sick leave totaled $12,807. The expenses for work by the infection control team totaled $1,408. The financial impact of this outbreak on hospital resources comprising loss of revenue and extra costs for microbiological diagnosis but without lost productivity costs, increased nursing care, and expenses for the infection control team totaled $40,675.

Nosocomial norovirus outbreaks result in significant loss of revenue and increased use of resources. Bed closures had a greater impact on hospital resources than increased need for nursing care.