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Hand hygiene compliance decreased significantly when opportunities exceeded 30 per hour. At higher workloads, the number of healthcare worker types involved and the proportion of hand hygiene opportunities for which physicians and other healthcare workers were responsible increased. Thus, care complexity and risk to patients may both increase with workload.
To determine whether the order in which healthcare workers perform patient care tasks affects hand hygiene compliance.
For this retrospective analysis of data collected during the Strategies to Reduce Transmission of Antimicrobial Resistant Bacteria in Intensive Care Units (STAR*ICU) study, we linked consecutive tasks healthcare workers performed into care sequences and identified task transitions: 2 consecutive task sequences and the intervening hand hygiene opportunity. We compared hand hygiene compliance rates and used multiple logistic regression to determine the adjusted odds for healthcare workers (HCWs) transitioning in a direction that increased or decreased the risk to patients if healthcare workers did not perform hand hygiene before the task and for HCWs contaminating their hands.
The study was conducted in 17 adult surgical, medical, and medical-surgical intensive care units.
HCWs in the STAR*ICU study units.
HCWs moved from cleaner to dirtier tasks during 5,303 transitions (34.7%) and from dirtier to cleaner tasks during 10,000 transitions (65.4%). Physicians (odds ratio [OR]: 1.50; P < .0001) and other HCWs (OR, 2.15; P < .0001) were more likely than nurses to move from dirtier to cleaner tasks. Glove use was associated with moving from dirtier to cleaner tasks (OR, 1.22; P < .0001). Hand hygiene compliance was lower when HCWs transitioned from dirtier to cleaner tasks than when they transitioned in the opposite direction (adjusted OR, 0.93; P < .0001).
HCWs did not organize patient care tasks in a manner that decreased risk to patients, and they were less likely to perform hand hygiene when transitioning from dirtier to cleaner tasks than the reverse. These practices could increase the risk of transmission or infection.
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: Assessing antimicrobial use (AU) appropriateness isa cornerstone of antimicrobial stewardship, largely accomplished through time-intensive manual chart review of specific agents or diagnoses. Efforts to evaluate appropriateness have focused on assessing the appropriateness of an entire treatment course. An electronic measure was developed to assess the appropriateness of each day of inpatient AU leveraging electronic health record data. Methods: We extracted contextual data, including risk factors for resistant organisms, allergies, constitutional signs and symptoms from diagnostic and procedural codes, and microbiological findings, from the electronic health records of patients in Veterans’ Health Administration inpatient wards reporting data to the National Healthcare Safety Network (NHSN) AU option from 2017–2018. Only the antibacterial categories shown in Figure 1 were included. Respiratory, urinary tract, skin and soft-tissue, and other infection categories were defined and applied to each hospital day. Algorithm rules were constructed to evaluate AU based on the clinical context (eg, in the ICU, during empiric therapy, drug–pathogen match, recommended drugs, and duration). Rules were drawn from available literature, were discussed with experts, and were then refined empirically. Generally, the rules allowed for use of first-line agents unless risk factors or contraindications were identified. AU was categorized as appropriate, inappropriate, or indeterminate for each day, then aggregated into an overall measure of facility-level AU appropriateness. A validation set of 20 charts were randomly selected for manual review. Results: Facility distribution of appropriateness, inappropriateness, and indeterminate AU by 4 of the adult, 2017 baseline NHSN Standardized Antimicrobial Administration Ratio (SAAR) categories are shown in Figure 1. The median facility-level inappropriateness across all SAAR categories was 37.2% (IQR, 29.4%–52.5%). The median facility-level indeterminate AU across all SAAR categories was 14.4% (IQR, 9.1%–21.2%). Chart review of 20 admissions showed agreement with algorithm appropriateness and inappropriateness in 95.4% of 240 antibacterial days.
Conclusions: We developed a comprehensive, flexible electronic tool to evaluate AU appropriateness for combinations of setting, antibacterial agent, syndrome, or time frame of interest (eg, empiric, definitive, or excess duration). Application of our algorithm in 2 years of VA acute-care data suggest substantial interfacility variability; the highest rates of inappropriateness were for anti-MRSA therapy. Our preliminary chart review demonstrated agreement between electronic and manual review in >95% of antimicrobial days. This approach may be useful to identify potential stewardship targets, in the development of decision support systems, and in conjunction with other metrics to track AU over time.
Healthcare-associated infections (HAIs) are a significant burden on healthcare facilities. Universal gloving is a horizontal intervention to prevent transmission of pathogens that cause HAI. In this meta-analysis, we aimed to identify whether implementation of universal gloving is associated with decreased incidence of HAI in clinical settings.
A systematic literature search was conducted to find all relevant publications using search terms for universal gloving and HAIs. Pooled incidence rate ratios (IRRs) and 95% confidence intervals (CIs) were calculated using random effects models. Heterogeneity was evaluated using the Woolf test and the I2 test.
In total, 8 studies were included. These studies were moderately to substantially heterogeneous (I2 = 59%) and had varied results. Stratified analyses showed a nonsignificant association between universal gloving and incidence of methicillin-resistant Staphylococcus aureus (MRSA; pooled IRR, 0.94; 95% CI, 0.79–1.11) and vancomycin-resistant enterococci (VRE; pooled IRR, 0.94; 95% CI, 0.69–1.28). Studies that implemented universal gloving alone showed a significant association with decreased incidence of HAI (IRR, 0.77; 95% CI, 0.67–0.89), but studies implementing universal gloving as part of intervention bundles showed no significant association with incidence of HAI (IRR, 0.95; 95% CI, 0.86–1.05).
Universal gloving may be associated with a small protective effect against HAI. Despite limited data, universal gloving may be considered in high-risk settings, such as pediatric intensive care units. Further research should be performed to determine the effects of universal gloving on a broader range of pathogens, including gram-negative pathogens.
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