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Background: Despite several measures to monitor and improve hand hygiene (HH) in health care settings, health care-acquired infections (HAIs) remain prevalent. The measures used to calculate HH performance are not able to fully benefit from the high-resolution data collected using electronic monitoring systems. Objective: This study proposes a novel parameter for quantifying the HAI exposure risk of individual patients by considering temporal and spatial features of health care workers’ HH adherence. Methods: Patient exposure risk is calculated as a function of the number of consecutive missed HH opportunities, the number of unique rooms visited by the health care professional, and the time duration that the health care professional spends inside and outside the patient’s room without performing HH. The patient exposure risk is compared to the entrance compliance rate (ECR) defined as the ratio of the number of HH actions performed at a room entrance to the total number of entrances into the room. The compliance rate is conventionally used to measure HH performance. The ECR and the patient exposure risk are analyzed using the data collected from an inpatient nursing unit for 12 weeks. Results: The analysis of data collected from 59 nurses and more than 25,600 records at a musculoskeletal rehabilitation unit at the Toronto Rehabilitation Institute, KITE, showed that there is no strong linear relation between the ECR and patient exposure risk (r=0.7, P<.001). Since the ECR is calculated based on the number of missed HH actions upon room entrance, this parameter is already included in the patient exposure risk. Therefore, there might be scenarios that these 2 parameters are correlated; however, in several cases, the ECR contrasted with the reported patient exposure risk. Generally, the patients in rooms with a significantly high ECR can be potentially exposed to a considerable risk of infection. By contrast, small ECRs do not necessarily result in a high patient exposure risk. The results clearly explained the important role of the factors incorporated in patient exposure risk for quantifying the risk of infection for the patients. Conclusions: Patient exposure risk might provide a more reliable estimation of the risk of developing HAIs compared to ECR by considering both the temporal and spatial aspects of HH records. [ABSTRACT FROM AUTHOR]

• Doctors (surgeons) have lower baseline hand hygiene compliance than nurses. • Light-guided nudging and data-driven performance feedback improve compliance. • Individual performance feedback might be more effective than group feedback. • The Sani nudge system detects more opportunities than using manual observations. • Nurses and doctors disinfect hands more often after rather than before patient contact. [Display omitted] Evidence-based practices to increase hand hygiene compliance (HHC) among health care workers are warranted. We aimed to investigate the effect of a multimodal strategy on HHC. During this 14-month prospective, observational study, an automated monitoring system was implemented in a 29-bed surgical ward. Hand hygiene opportunities and alcohol-based hand rubbing events were measured in patient and working rooms (medication, utility, storerooms, toilets). We compared baseline HHC of health care workers across periods with light-guided nudging from sensors on dispensers and data-driven performance feedback (multimodal strategy) using the Student's t test. The doctors (n = 10) significantly increased their HHC in patient rooms (16% vs 42%, P <.0001) and working rooms (24% vs 78%, P =.0006) when using the multimodal strategy. The nurses (n = 26) also increased their HHC significantly from baseline in both patient rooms (27% vs 43%, P =.0005) and working rooms (39% vs 64%, P <.0001). The nurses (n = 9), who subsequently received individual performance feedback, further increased HHC, compared with the period when they received group performance feedback (patient rooms: 43% vs 55%, P <.0001 and working rooms: 64% vs 80%, P <.0001). HHC of doctors and nurses can be significantly improved with light-guided nudging and data-driven performance feedback using an automated hand hygiene system. [ABSTRACT FROM AUTHOR]

Image, graphical abstract Hand hygiene compliance (HHC) among health care workers remains suboptimal, and good monitoring systems are lacking. We aimed to evaluate HHC using an automated monitoring system. A prospective, observational study was conducted at 2 Danish university hospitals employing a new monitoring system (Sani nudge). Sensors were located on alcohol-based sanitizers, health care worker name tags, and patient beds measuring hand hygiene opportunities and sanitations. In total, 42 nurses were included with an average HHC of 52% and 36% in hospitals A and B, respectively. HHC was lowest in patient rooms (hospital A: 45%; hospital B: 29%) and highest in staff toilets (hospital A: 72%; hospital B: 91%). Nurses sanitized after patient contact more often than before, and sanitizers located closest to room exits and in hallways were used most frequently. There was no association found between HHC level and the number of beds in patient rooms. The HHC level of each nurse was consistent over time, and showed a positive correlation between the number of sanitations and HHC levels (hospital A: r = 0.69; hospital B: r = 0.58). The Sani nudge system can be used to monitor HHC at individual and group levels, which increases the understanding of compliance behavior. [ABSTRACT FROM AUTHOR]

Background Poor hand hygiene by health care workers is a major cause of nosocomial infections. This research evaluated the ability of an electronic monitoring system with real-time prompting capability to change hand hygiene behaviors. Methods Handwashing activity was measured by counting dispenser activations on a single nursing unit before, during, and after installation of the system. The effect of changing the prompt duration on hand hygiene performance was determined by a cluster-randomized trial on 3 nursing units with 1 acting as control. Sustainability of performance and participation was observed on 4 nursing units over a year. All staff were eligible to participate. Results Between June 2015 and December 2016, a total of 459,376 hand hygiene opportunities and 330,740 handwashing events from 511 staff members were recorded. Dispenser activation counts were significantly influenced by use of the system (χ 2 [3] = 75.76; P  < .0001). Hand hygiene performance dropped from 62.61% to 24.94% (odds ratio, 0.36; 95% confidence interval, 0.34-0.38) when the prompting feature was removed. Staff participation had a negative trajectory of –0.72% ( P  < .001), whereas change in average performance was –0.18% ( P  < .001) per week for the year. Conclusions Use of electronic monitoring with real-time prompts of 20 seconds' duration nearly doubles handwashing activity and causes handwashing to occur sooner after entering a patient room. These improvements are sustainable over a year. [ABSTRACT FROM AUTHOR]