Resistant gram-negative bacteria (R-GNB) colonization in nursing home patients can cause clinical infection and intrafacility transmission. Limited data exist on the roles of age and function on R-GNB colonization.

A secondary data analysis was performed from a cohort study of 896 patients admitted to 6 Michigan nursing homes between November 2013 and May 2018. Swabs obtained upon enrollment, weekly for 1 month, then monthly until nursing home discharge from 5 anatomical sites were cultured for GNB. R-GNB were defined as resistant to ciprofloxacin, ceftazidime, or imipenem. Patients with growth of the same R-GNB as the initial positive visit, from any anatomical site at any subsequent visit, were considered persistently colonized. Demographic data, antibiotic use, device use, and physical self-maintenance scales (PSMSs) were obtained upon enrollment. Characteristics were compared between patients with R-GNB colonization versus those without, and those with persistent R-GNB colonization versus those with spontaneous decolonization.

Of 169 patients with a positive R-GNB culture and ≥2 subsequent study visits, 89 (53%) were transiently colonized and 80 (47%) were persistently colonized. Compared to uncolonized patients, persistent and transient R-GNB colonization were associated with higher PSMS score: 1.14 (95% confidence interval or CI, 1.05–1.23; P = .002) and 1.10 (95% CI, 1.01–1.19; P = .023), respectively. Persistent colonization was independently associated with longer duration of nursing home stay (1.02; 95% CI, 1.01–1.02; P < .001). Higher readmission rate among persistently colonized patients was observed on unadjusted analysis.

Persistent R-GNB colonization is associated with younger age, functional disability, and prolonged length of nursing home stay. In-depth longitudinal studies to understand new acquisition and transmission dynamics of R-GNB in nursing homes are needed.

To describe the genomic analysis and epidemiologic response related to a slow and prolonged methicillin-resistant Staphylococcus aureus (MRSA) outbreak.

Prospective observational study.

Neonatal intensive care unit (NICU).

We conducted an epidemiologic investigation of a NICU MRSA outbreak involving serial baby and staff screening to identify opportunities for decolonization. Whole-genome sequencing was performed on MRSA isolates.

A NICU with excellent hand hygiene compliance and longstanding minimal healthcare-associated infections experienced an MRSA outbreak involving 15 babies and 6 healthcare personnel (HCP). In total, 12 cases occurred slowly over a 1-year period (mean, 30.7 days apart) followed by 3 additional cases 7 months later. Multiple progressive infection prevention interventions were implemented, including contact precautions and cohorting of MRSA-positive babies, hand hygiene observers, enhanced environmental cleaning, screening of babies and staff, and decolonization of carriers. Only decolonization of HCP found to be persistent carriers of MRSA was successful in stopping transmission and ending the outbreak. Genomic analyses identified bidirectional transmission between babies and HCP during the outbreak.

In comparison to fast outbreaks, outbreaks that are “slow and sustained” may be more common to units with strong existing infection prevention practices such that a series of breaches have to align to result in a case. We identified a slow outbreak that persisted among staff and babies and was only stopped by identifying and decolonizing persistent MRSA carriage among staff. A repeated decolonization regimen was successful in allowing previously persistent carriers to safely continue work duties.

Asynchronous virtual patient care is increasingly used; however, the effectiveness of virtually delivering guideline-concordant care in conjunction with antibiotic stewardship initiatives remains uncertain. We developed a bundled stewardship intervention to improve antibiotic use in E-visits for upper respiratory tract infections (URTIs).

In this before-and-after study, adult patients who completed E-visits for “cough,” “flu,” or “sinus symptoms” at Michigan Medicine between January 1, 2018, and September 30, 2020, were included. Patient demographics, diagnoses, and antibiotic details were collected. The multifaceted intervention occurred over 6 months. Segmented linear regression was performed to estimate the effect of the intervention on appropriate antibiotic use for URTI diagnoses (defined as no antibiotic prescribed) and sinusitis (defined as guideline-concordant antibiotic selection and duration). Regression lines were fit to data before the bundled intervention (January 2019) and after the bundled intervention (May 2019).

In total, 5,151 E-visits were included. The intervention decreased the number of visits for flu, cough, or sinus symptoms prescribed antibiotics from 43.2% to 28.9% (P < .001). Guideline concordance of antibiotic prescriptions improved following the intervention: first-line amoxicillin-clavulanate rose from 37.9% of prescriptions to 66.1% of prescriptions (P < .001), second-line doxycycline rose from 13.8% to 22.7% (P < .001); and median duration of antibiotics decreased from 10 days to 5 days (P < .001).

A multifaceted stewardship bundle for E-visits involving both changes in the EMR and audit and feedback improved guideline-concordant antibiotic use for URTIs. This approach can aid stewardship efforts in the ambulatory care setting with regard to telemedicine.

In the era of widespread resistance, there are 2 time points at which most empiric prescription errors occur among hospitalized adults: (1) upon admission (UA) when treating patients at risk of multidrug-resistant organisms (MDROs) and (2) during hospitalization, when treating patients at risk of extensively drug-resistant organisms (XDROs). These errors adversely influence patient outcomes and the hospital’s ecology.

Retrospective cohort study, Shamir Medical Center, Israel, 2016.

Adult patients (aged >18 years) hospitalized with sepsis.

Logistic regressions were used to develop predictive models for (1) MDRO UA and (2) nosocomial XDRO. Their performances on the derivation data sets, and on 7 other validation data sets, were assessed using the area under the receiver operating characteristic curve (ROC AUC).

In total, 4,114 patients were included: 2,472 patients with sepsis UA and 1,642 with nosocomial sepsis. The MDRO UA score included 10 parameters, and with a cutoff of ≥22 points, it had an ROC AUC of 0.85. The nosocomial XDRO score included 7 parameters, and with a cutoff of ≥36 points, it had an ROC AUC of 0.87. The range of ROC AUCs for the validation data sets was 0.7–0.88 for the MDRO UA score and was 0.66–0.75 for nosocomial XDRO score. We created a free web calculator (https://assafharofe.azurewebsites.net).

A simple electronic calculator could aid with empiric prescription during an encounter with a septic patient. Future implementation studies are needed to evaluate its utility in improving patient outcomes and in reducing overall resistances.

Prolonged survival of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on environmental surfaces and personal protective equipment may lead to these surfaces transmitting this pathogen to others. We sought to determine the effectiveness of a pulsed-xenon ultraviolet (PX-UV) disinfection system in reducing the load of SARS-CoV-2 on hard surfaces and N95 respirators.

Chamber slides and N95 respirator material were directly inoculated with SARS-CoV-2 and were exposed to different durations of PX-UV.

For hard surfaces, disinfection for 1, 2, and 5 minutes resulted in 3.53 log10, >4.54 log10, and >4.12 log10 reductions in viral load, respectively. For N95 respirators, disinfection for 5 minutes resulted in >4.79 log10 reduction in viral load. PX-UV significantly reduced SARS-CoV-2 on hard surfaces and N95 respirators.

With the potential to rapidly disinfectant environmental surfaces and N95 respirators, PX-UV devices are a promising technology to reduce environmental and personal protective equipment bioburden and to enhance both healthcare worker and patient safety by reducing the risk of exposure to SARS-CoV-2.

Antibiotic-resistant organism (ARO) colonization rates in skilled nursing facilities (NFs) are high; hand hygiene is crucial to interrupt transmission. We aimed to determine factors associated with hand hygiene adherence in NFs and to assess rates of ARO acquisition among healthcare personnel (HCP).

HCP were observed during routine care at 6 NFs. We recorded hand hygiene adherence, glove use, activities, and time in room. HCP hands were cultured before and after patient care; patients and high-touch surfaces were cultured. HCP activities were categorized as high-versus low-risk for self-contamination. Multivariable regression was performed to identify predictors of hand hygiene adherence.

We recorded 385 HCP observations and paired them with cultures performed before and after patient care. Hand hygiene adherence occurred in 96 of 352 observations (27.3%) before patient care and 165 of 358 observations (46.1%) after patient care. Gloves were worn in 169 of 376 observations (44.9%). Higher adherence was associated with glove use before patient care (odds ratio [OR], 2.55; 95% confidence interval [CI], 1.44–4.54) and after patient care (OR, 3.11; 95% CI, 1.77–5.48). Compared with nurses, certified nurse assistants had lower hand hygiene adherence (OR, 0.31; 95% CI, 0.15–0.67) before patient care and physical/occupational therapists (OR, 0.22; 95% CI, 0.11–0.44) after patient care. Hand hygiene varied by activity performed and time in the room. HCP hands were contaminated with AROs in 35 of 385 cultures of hands before patient care (0.9%) and 22 of 350 cultures of hands after patient care (6.3%).

Hand hygiene adherence in NFs remain low; it is influenced by job title, type of care activity, and glove use. Hand hygiene programs should incorporate these unique care and staffing factors to reduce ARO transmission.

Risk adjustment is needed to fairly compare central-line–associated bloodstream infection (CLABSI) rates between hospitals. Until 2017, the Centers for Disease Control and Prevention (CDC) methodology adjusted CLABSI rates only by type of intensive care unit (ICU). The 2017 CDC models also adjust for hospital size and medical school affiliation. We hypothesized that risk adjustment would be improved by including patient demographics and comorbidities from electronically available hospital discharge codes.

Using a cohort design across 22 hospitals, we analyzed data from ICU patients admitted between January 2012 and December 2013. Demographics and International Classification of Diseases, Ninth Edition, Clinical Modification (ICD-9-CM) discharge codes were obtained for each patient, and CLABSIs were identified by trained infection preventionists. Models adjusting only for ICU type and for ICU type plus patient case mix were built and compared using discrimination and standardized infection ratio (SIR). Hospitals were ranked by SIR for each model to examine and compare the changes in rank.

Overall, 85,849 ICU patients were analyzed and 162 (0.2%) developed CLABSI. The significant variables added to the ICU model were coagulopathy, paralysis, renal failure, malnutrition, and age. The C statistics were 0.55 (95% CI, 0.51–0.59) for the ICU-type model and 0.64 (95% CI, 0.60–0.69) for the ICU-type plus patient case-mix model. When the hospitals were ranked by adjusted SIRs, 10 hospitals (45%) changed rank when comorbidity was added to the ICU-type model.

Our risk-adjustment model for CLABSI using electronically available comorbidities demonstrated better discrimination than did the CDC model. The CDC should strongly consider comorbidity-based risk adjustment to more accurately compare CLABSI rates across hospitals.

Infect Control Hosp Epidemiol 2017;38:1019–1024