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Background: Certain nursing home (NH) resident care tasks have a higher risk for multidrug-resistant organisms (MDRO) transfer to healthcare personnel (HCP), which can result in transmission to residents if HCPs fail to perform recommended infection prevention practices. However, data on HCP-resident interactions are limited and do not account for intrafacility practice variation. Understanding differences in interactions, by HCP role and unit, is important for informing MDRO prevention strategies in NHs. Methods: In 2019, we conducted serial intercept interviews; each HCP was interviewed 6–7 times for the duration of a unit’s dayshift at 20 NHs in 7 states. The next day, staff on a second unit within the facility were interviewed during the dayshift. HCP on 38 units were interviewed to identify healthcare personnel (HCP)–resident care patterns. All unit staff were eligible for interviews, including certified nursing assistants (CNAs), nurses, physical or occupational therapists, physicians, midlevel practitioners, and respiratory therapists. HCP were asked to list which residents they had cared for (within resident rooms or common areas) since the prior interview. Respondents selected from 14 care tasks. We classified units into 1 of 4 types: long-term, mixed, short stay or rehabilitation, or ventilator or skilled nursing. Interactions were classified based on the risk of HCP contamination after task performance. We compared proportions of interactions associated with each HCP role and performed clustered linear regression to determine the effect of unit type and HCP role on the number of unique task types performed per interaction. Results: Intercept-interviews described 7,050 interactions and 13,843 care tasks. Except in ventilator or skilled nursing units, CNAs have the greatest proportion of care interactions (interfacility range, 50%–60%) (Fig. 1). In ventilator and skilled nursing units, interactions are evenly shared between CNAs and nurses (43% and 47%, respectively). On average, CNAs in ventilator and skilled nursing units perform the most unique task types (2.5 task types per interaction, Fig. 2) compared to other unit types (P < .05). Compared to CNAs, most other HCP types had significantly fewer task types (0.6–1.4 task types per interaction, P < .001). Across all facilities, 45.6% of interactions included tasks that were higher-risk for HCP contamination (eg, transferring, wound and device care, Fig. 3). Conclusions: Focusing infection prevention education efforts on CNAs may be most efficient for preventing MDRO transmission within NH because CNAs have the most HCP–resident interactions and complete more tasks per visit. Studies of HCP-resident interactions are critical to improving understanding of transmission mechanisms as well as target MDRO prevention interventions.
Funding: Centers for Disease Control and Prevention (grant no. U01CK000555-01-00)
Disclosures: Scott Fridkin, consulting fee, vaccine industry (spouse)
Background: Contamination of healthcare workers and patient environments likely play a role in the spread of antibiotic-resistant organisms. The mechanisms that contribute to the distribution of organisms within and between patient rooms are not well understood, but they may include movement patterns and patient interactions of healthcare workers. We used an innovative technology for tracking healthcare worker movement and patient interactions in ICUs. Methods: The Kinect system, a device developed by Microsoft, was used to detect the location of a person’s hands and head over time, each represented with 3-dimensional coordinates. The Kinects were deployed in 2 intensive care units (ICUs), at 2 different hospitals, and they collected data from 5 rooms in a high-acuity 20-bed cardiovascular ICU (unit 1) and 3 rooms in a 10-bed medical-surgical ICU (unit 2). The length of the Kinect deployment varied by room (range, 15–48 days). The Kinect data were processed to included date, time, and location of head and hands for all individuals. Based on the coordinates of the bed, we defined events indicating bed touch, distance 30 cm (1 foot) from the bed, and distance 1 m (3 feet) from the bed. The processed Kinect data were then used to generate heat maps showing density of person locations within a room and summarizing bed touches and time spent in different locations within the room. Results: The Kinect systems captured In total, 2,090 hours of room occupancy by at least 1 person within ~1 m of the bed (Table 1). Approximately half of the time spent within ~1 m from the bed was at the bedside (within ~30 cm). The estimated number of bed touches per hour when within ~1 m was 13–23. Patients spent more time on one side of the bed, which varied by room and facility (Fig. 1A, 1B). Additionally, we observed temporal variation in intensity measured by person time in the room (Fig. 1C, 1D). Conclusions: High occupancy tends to be on the far side (away from the door) of the patient bed where the computers are, and the bed touch rate is relatively high. These results can be used to help us understand the potential for room contamination, which can contribute to both transmission and infection, and they highlight critical times and locations in the room, with a potential for focused deep cleaning.
Determine the effectiveness of a personal protective equipment (PPE)-free zone intervention on healthcare personnel (HCP) entry hand hygiene (HH) and PPE donning compliance in rooms of patients in contact precautions.
Quasi-experimental, multicenter intervention, before-and-after study with concurrent controls.
All patient rooms on contact precautions on 16 units (5 medical-surgical, 6 intensive care, 5 specialty care units) at 3 acute-care facilities (2 academic medical centers, 1 Veterans Affairs hospital). Observations of PPE donning and entry HH compliance by HCP were conducted during both study phases. Surveys of HCP perceptions of the PPE-free zone were distributed in both study phases.
A PPE-free zone, where a low-risk area inside door thresholds of contact precautions rooms was demarcated by red tape on the floor. Inside this area, HCP were not required to wear PPE.
We observed 3,970 room entries. HH compliance did not change between study phases among intervention units (relative risk [RR], 0.92; P = .29) and declined in control units (RR, 0.70; P = .005); however, the PPE-free zone did not significantly affect compliance (P = .07). The PPE-free zone effect on HH was significant only for rooms on enteric precautions (P = .008). PPE use was not significantly different before versus after the intervention (P = .15). HCP perceived the zone positively; 65% agreed that it facilitated communication and 66.8% agreed that it permitted checking on patients more frequently.
HCP viewed the PPE-free zone favorably and it did not adversely affect PPE or HH compliance. Future infection prevention interventions should consider the complex sociotechnical system factors influencing behavior change.
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