This study aims to outline Clostridioides difficile infection (CDI) trends and outcomes in Mexican healthcare facilities during the COVID-19 pandemic.

Observational study of case series.

Sixteen public hospitals and private academic healthcare institutions across eight states in Mexico from January 2016 to December 2022.

CDI patients.

Demographic, clinical, and laboratory data of CDI patients were obtained from clinical records. Cases were classified as community or healthcare-associated infections, with incidence rates calculated as cases per 10,000 patient days. Risk factors for 30-day all-cause mortality were analyzed by multivariate logistic regression.

We identified 2,356 CDI cases: 2,118 (90%) were healthcare-associated, and 232 (10%) were community-associated. Common comorbidities included hypertension, diabetes, and cancer. Previous high use of proton-pump inhibitors, steroids, and antibiotics was observed. Recurrent infection occurred in 112 (5%) patients, and 30-day mortality in 371 (16%). Risk factors associated with death were a high Charlson score, prior use of steroids, concomitant use of antibiotics, leukopenia, leukocytosis, elevated serum creatine, hypoalbuminemia, septic shock or abdominal sepsis, and SARS-CoV-2 coinfection. The healthcare-associated CDI incidence remained stable at 4.78 cases per 10,000 patient days during the pre-and pandemic periods. However, the incidence was higher in public hospitals.

Our study underscores the need for routine epidemiology surveillance and standardized CDI classification protocols in Mexican institutions. Though CDI rates in our country align with those in some European countries, disparities between public and private healthcare sectors emphasize the importance of targeted interventions.

The economic burden of Clostridioides difficile infection (CDI) is considerable and mostly associated with a high frequency of hospitalizations. Numerous publications have demonstrated that CDI is associated with a higher risk of hospital readmission, but not always a specific rate or attributable to disease recurrence.

In this systematic review, we describe the incidence of 30-day CDI-associated readmission rates and the effect of active interventions. Three search engines were utilized for the literature search, and a total of 9 studies were included in this review. Hospital readmission proportions from interventional and observational studies were analyzed through meta-analysis with random effects.

Two thousand five hundred and twenty-one articles were identified. After screening full-text articles, 9 eligible articles published between 2002 and 2023 met the inclusion criteria. In total, 132,862 CDI patients were evaluated. Thirty-day CDI-associated readmissions were defined as either an ICD9/10 code indicating CDI admission with a prior admission within the past 30 days (n = 4) or a medical chart evaluation of signs and symptoms consistent with CDI (diarrhea) along with a positive diagnostic test (n = 5) with a prior hospitalization for CDI within the past 30 days. Meta-analysis of observational studies estimated 30-day CDI readmissions were 6% (95% CI, 5%–7%). Three studies evaluated the effect of active interventions to reduce CDI-associated 30-day readmission rates. Two of 3 interventions reduced the likelihood of CDI-associated 30-day readmissions.

This systematic review identified a 6% rate of 30-day CDI-associated hospital readmission. Antimicrobial stewardship efforts and the use of specific therapeutics were shown to reduce these rates.

Evaluation of adult antibiotic order sets (AOSs) on antibiotic stewardship metrics has been limited. The primary outcome was to evaluate the standardized antimicrobial administration ratio (SAAR). Secondary outcomes included antibiotic days of therapy (DOT) per 1,000 patient days (PD); selected antibiotic use; AOS utilization; Clostridioides difficile infection (CDI) cases; and clinicians’ perceptions of the AOS via a survey following the final study phase.

This 5-year, single-center, quasi-experimental study comprised 5 phases from 2017 to 2022 over 10-month periods between August 1 and May 31.

The study was conducted in a 752-bed tertiary care, academic medical center.

Our institution implemented AOSs in the electronic medical record (EMR) for common infections among hospitalized adults.

For the primary outcome, a statistically significant decreases in SAAR were detected from phase 1 to phase 5 (1.0 vs 0.90; P < .001). A statistically significant decreases were detected in DOT per 1,000 PD (4,884 vs 3,939; P = .001), fluoroquinolone orders (407 vs 175; P < .001), carbapenem orders (147 vs 106; P = .024), and clindamycin orders (113 vs 73; P = .01). No statistically significant change in mean vancomycin orders was detected (991 vs 902; P = .221). A statistically significant decrease in CDI cases was also detected (7.8, vs 2.4; P = .002) but may have been attributable to changes in CDI case diagnosis. Clinicians indicated that the AOSs were easy to use overall and that they helped them select the appropriate antibiotics.

Implementing AOS into the EMR was associated with a statistically significant reduction in SAAR, antibiotic DOT per 1,000 PD, selected antibiotic orders, and CDI cases.

The days of therapy (DOT) metric, used to estimate antimicrobial consumption, has some limitations. Days of antibiotic spectrum coverage (DASC), a novel metric, overcomes these limitations. We examined the difference between these 2 metrics of inpatient intravenous antimicrobial consumption in assessing antimicrobial stewardship efficacy and antimicrobial resistance using vector autoregressive (VAR) models with time-series analysis.

Differences between DOT and DASC were investigated at a tertiary-care center over 8 years using VAR models with 3 variables in the following order: (1) the monthly proportion of prospective audit and feedback (PAF) acceptance as an index of antimicrobial stewardship efficacy; (2) monthly DOT and DASC adjusted by 1,000 days present as indices of antimicrobial consumption; and (3) the monthly incidence of 5 organisms as an index of antimicrobial resistance.

The Granger causality test, which evaluates whether incorporating lagged variables can help predict other variables, showed that PAF activity contributed to DOT and DASC, which, in turn, contributed to the incidence of drug-resistant P. aeruginosa. Notably, only DASC helped predict the incidence of drug-resistant Enterobacterales. Another VAR analysis demonstrated that a high proportion of PAF acceptance was accompanied by decreased DASC in a given month, whereas increased DASC was accompanied by an increased incidence of drug-resistant Enterobacterales, unlike with DOT.

The VAR models of PAF activity, antimicrobial consumption, and antimicrobial resistance suggested that DASC may more accurately reflect the impact of PAF on antimicrobial consumption and be superior to DOT for predicting the incidence of drug-resistant Enterobacterales.

Despite the increasing rates of carbapenem-resistant Acinetobacter baumannii (CRAB) carriage among hospitalized patients in endemic settings, the role of active surveillance cultures and cohorting is still debated. We sought to determine the long-term effect of a multifaceted infection-control intervention on the incidence of CRAB in an endemic setting.

A prospective, quasi-experimental study was performed at a 670-bed, acute-care hospital. The study consisted of 4 phases. In phase I, basic infection control measures were used. In phase II, CRAB carriers were cohorted in a single ward with dedicated nursing and enhanced environmental cleaning. In phase III large-scale screening in high-risk units was implemented. Phase IV comprised a 15-month follow-up period.

During the baseline period, the mean incidence rate (IDR) of CRAB was 44 per 100,000 patient days (95% CI, 37.7–54.1). No significant decrease was observed during phase II (IDR, 40.8 per 100,000 patient days; 95% CI, 30.0–56.7; P = .97). During phase III, despite high compliance with control measures, ongoing transmission in several wards was observed and the mean IDR was 53.9 per 100,000 patient days (95% CI, 40.5–72.2; P = .55). In phase IV, following the implementation of large-scale screening, a significant decrease in the mean IDR was observed (25.8 per 100,000 patient days; 95% CI, 19.9–33.5; P = .03). An overall reduction of CRAB rate was observed between phase I and phase IV (rate ratio, 0.6; 95% CI, 0.4–0.9; P < .001).

The comprehensive intervention that included intensified control measures with routine active screening cultures was effective in reducing the incidence of CRAB in an endemic hospital setting.

Klebsiella pneumoniae are common pathogens causing bloodstream infection (BSI) that increasingly express carbapenem resistance worldwide. To date, no study has precisely investigated the impact of carbapenem resistance in K. pneumoniae (CRKP) BSI on mortality.

This retrospective study included 87 patients with CRKP BSI and 321 patients with carbapenem-susceptible K. pneumoniae (CSKP) BSI from 2015 to 2020. Propensity score analyses with stabilized inverse probability of treatment weighting (IPTW-S) was applied to balance covariates. The hazard ratio for 30-day mortality associated with carbapenem resistance was estimated using Cox regression and Kaplan-Meier curves.

The 30-day crude mortality rates were 43.7% in patients with CRKP BSI and 17.8% in patients with CSKP BSI (P < .001). Age ≥55 years, underlying hematological malignancies and hemodialysis were independently associated with mortality in CRKP BSI. A skin or soft-tissue infection source, urinary catheter, and underlying chronic obstructive pulmonary disease were predictors of mortality in CSKP BSI. The group characteristics were well balanced after IPTW-S. The adjusted hazard ratio for 30-day mortality for CRKP BSI was 1.607 (interquartile range, 0.814–3.171).

Carbapenem resistance was not associated with a significant increase in 30-day mortality in KP BSI; patient and disease factors were primary determinants of outcomes.

To assess the relative risk of hospital-onset Clostridioides difficile (HO-CDI) during each month of the early coronavirus disease 2019 (COVID-19) pandemic and to compare it with historical expectation based on patient characteristics.

This study used a retrospective cohort design. We collected secondary data from the institution’s electronic health record (EHR).

The Ohio State University Wexner Medical Center, Ohio, a large tertiary healthcare system in the Midwest.

All adult patients admitted to the inpatient setting between January 2018 and May 2021 were eligible for the study. Prisoners, children, individuals presenting with Clostridioides difficile on admission, and patients with <4 days of inpatient stay were excluded from the study.

After controlling for patient characteristics, the observed numbers of HO-CDI cases were not significantly different than expected. However, during 3 months of the pandemic period, the observed numbers of cases were significantly different from what would be expected based on patient characteristics. Of these 3 months, 2 months had more cases than expected and 1 month had fewer.

Variations in HO-CDI incidence seemed to trend with COVID-19 incidence but were not fully explained by our case mix. Other factors contributing to the variability in HO-CDI incidence beyond listed patient characteristics need to be explored.

Dispersal of gram-negative bacilli from sink drains has been implicated as a source of transmission in multiple outbreaks.

In an acute care hospital, we assessed how often patient care supplies and other frequently touched items were within 1 meter of sink drains. We tested the efficacy of a ceiling-mounted far ultraviolet-C (UV-C) light technology for decontamination of sink bowls and surfaces near sinks with and without a wall-mounted film that reflects far UV-C light.

Of 190 sinks assessed, 55 (29%) had patient care supplies or other frequently touched items within 1 meter of the drain. The far UV-C technology reduced Pseudomonas aeruginosa, Enterobacter cloacae and Candida auris on steel disk carriers by ≥1.5 log10 colony-forming units (CFU) in 45 minutes. On inoculated real-world items, ≥1.9 log10 CFU reductions in P. aeruginosa were achieved on sites in line with the light source versus 0.4–1.8 log10 CFU reductions on shaded surfaces. The addition of the reflective surface significantly enhanced efficacy in shaded sites (P < 0.01).

In a hospital setting, patient care supplies and other frequently touched items were often in proximity to sinks. The far UV-C light technology could potentially be useful for sink decontamination in high-risk areas.

Understanding characteristics of healthcare personnel (HCP) with SARS-CoV-2 infection supports the development and prioritization of interventions to protect this important workforce. We report detailed characteristics of HCP who tested positive for SARS-CoV-2 from April 20, 2020 through December 31, 2021.

CDC collaborated with Emerging Infections Program sites in 10 states to interview HCP with SARS-CoV-2 infection (case-HCP) about their demographics, underlying medical conditions, healthcare roles, exposures, personal protective equipment (PPE) use, and COVID-19 vaccination status. We grouped case-HCP by healthcare role. To describe residential social vulnerability, we merged geocoded HCP residential addresses with CDC/ATSDR Social Vulnerability Index (SVI) values at the census tract level. We defined highest and lowest SVI quartiles as high and low social vulnerability, respectively.

Our analysis included 7,531 case-HCP. Most case-HCP with roles as certified nursing assistant (CNA) (444, 61.3%), medical assistant (252, 65.3%), or home healthcare worker (HHW) (225, 59.5%) reported their race and ethnicity as either non-Hispanic Black or Hispanic. More than one third of HHWs (166, 45.2%), CNAs (283, 41.7%), and medical assistants (138, 37.9%) reported a residential address in the high social vulnerability category. The proportion of case-HCP who reported using recommended PPE at all times when caring for patients with COVID-19 was lowest among HHWs compared with other roles.

To mitigate SARS-CoV-2 infection risk in healthcare settings, infection prevention, and control interventions should be specific to HCP roles and educational backgrounds. Additional interventions are needed to address high social vulnerability among HHWs, CNAs, and medical assistants.

Knowledge of local antibiotic resistance data, provided by antibiograms (a cumulative summary of in vitro-antimicrobial-susceptibility-test results), can aid prescribing of appropriate empirical antibiotics. This study aimed to explore the feasibility of antibiogram development for residential aged care facilities (RACFs).

Retrospective observational study of culture and sensitivity data.

Nine RACFs in Queensland, Australia.

Available antimicrobial susceptibility results were collected retrospectively for all residents of recruited RACFs from January 1, 2020, to December 31, 2022. Data were managed and analyzed with WHONET software®, and antibiograms were developed in accordance with the CLSI-M39 guidelines. Antibiogram data beyond the standard 12-months and pooling of data from geographically similar RACFs were explored as options to improve feasibility and validity of the antibiograms.

The most prevalent bacteria in the RACFs were Escherichia coli and Staphylococcus aureus. Due to the low number of positive cultures (less than 30) for individual RACFs, an annual antibiogram was not feasible. Extending the time-period to three years improved feasibility of antibiograms for E.coli in seven RACFs and S.aureus in five RACFs. Combining the data from closely located RACFs allowed for sufficient urinary and skin swab isolates to produce annual pooled antibiograms for all three years.

Use of extended time period antibiograms can provide RACF specific urinary and skin/soft tissue resistance data without the necessity of private pathology provider input. However, pooled syndromic antibiograms can be made available on an annual basis, which may be the preferred option.

To evaluate the impact of an intervention to limit dispersal from wastewater drain (WWD) sites on meropenem-nonsusceptible Pseudomonas aeruginosa patient and environmental colonization and bloodstream infection (BSI) on a hematopoietic cell transplant (HCT) and hematologic malignancy (HM) unit.

This quasi-experimental study included pre/postintervention point-prevalence surveys in July 2019 and June 2020, respectively. The retrospective cohort included HCT/HM patients with P. aeruginosa BSI between 2012 and 2022.

Adult HCT/HM unit at an academic center.

This study included consenting HCT/HM patients on the unit at the time of the point-prevalence surveys. HCT/HM patients with P. aeruginosa BSI between 2012 and 2022.

A quality improvement intervention targeting WWD sites was conceived and implemented on a HCT/HM unit. Pre and postintervention colonization samples were obtained from patients and environmental sites, cultivated on selective media, then characterized by susceptibility testing. Whole-genome sequencing and phylogenetic analysis were performed on select isolates. The impact of the intervention on colonization and BSI was evaluated, as was relatedness among isolates.

Although colonization of WWD sites with meropenem-nonsusceptible P. aeruginosa was widespread before and after this intervention, we observed a substantial decline in patient colonization (prevalence rate ratio, 0.35; 95% confidence interval [CI], 0.04–3.12) and BSI (incidence rate ratio, 0.67; 95% CI, 0.31–1.42) after the intervention. Among 3 predominant sequence types (ST-111, ST-446, and ST-308), there was striking genetic conservation within groups and among environmental colonization, patient colonization, and BSI isolates.

An intervention targeting WWD sites on a HCT/HM unit had a meaningful impact on meropenem-nonsusceptible P. aeruginosa patient colonization and BSI.

To evaluate the impact of changes in the size and characteristics of the hospitalized patient population during the COVID-19 pandemic on the incidence of hospital-associated Clostridioides difficile infection (HA-CDI).

Interrupted time-series analysis.

A 576-bed academic medical center in Portland, Oregon.

We established March 23, 2020 as our pandemic onset and included 24 pre-pandemic and 24 pandemic-era 30-day intervals. We built an autoregressive segmented regression model to evaluate immediate and gradual changes in HA-CDI rate during the pandemic while controlling for changes in known CDI risk factors.

We observed 4.5 HA-CDI cases per 10,000 patient-days in the two years prior to the pandemic and 4.7 cases per 10,000 patient-days in the first two years of the pandemic. According to our adjusted segmented regression model, there were neither significant changes in HA-CDI rate at the onset of the pandemic (level-change coefficient = 0.70, P-value = 0.57) nor overtime during the pandemic (slope-change coefficient = 0.003, P-value = 0.97). We observed significant increases in frequency and intensity of antibiotic use, time at risk, comorbidities, and patient age before and after the pandemic onset. Frequency of C. difficile testing did not significantly change during the pandemic (P= 0.72).

Despite large increases in several CDI risk factors, we did not observe the expected corresponding changes in HA-CDI rate during the first two years of the COVID-19 pandemic. We hypothesize that infection prevention measures responding to COVID-19 played a role in CDI prevention.

To evaluate the incidence of a candidate definition of healthcare facility-onset, treated Clostridioides difficile (CD) infection (cHT-CDI) and to identify variables and best model fit of a risk-adjusted cHT-CDI metric using extractable electronic heath data.

We analyzed 9,134,276 admissions from 265 hospitals during 2015–2020. The cHT-CDI events were defined based on the first positive laboratory final identification of CD after day 3 of hospitalization, accompanied by use of a CD drug. The generalized linear model method via negative binomial regression was used to identify predictors. Standardized infection ratios (SIRs) were calculated based on 2 risk-adjusted models: a simple model using descriptive variables and a complex model using descriptive variables and CD testing practices. The performance of each model was compared against cHT-CDI unadjusted rates.

The median rate of cHT-CDI events per 100 admissions was 0.134 (interquartile range, 0.023–0.243). Hospital variables associated with cHT-CDI included the following: higher community-onset CDI (CO-CDI) prevalence; highest-quartile length of stay; bed size; percentage of male patients; teaching hospitals; increased CD testing intensity; and CD testing prevalence. The complex model demonstrated better model performance and identified the most influential predictors: hospital-onset testing intensity and prevalence, CO-CDI rate, and community-onset testing intensity (negative correlation). Moreover, 78% of the hospitals ranked in the highest quartile based on raw rate shifted to lower percentiles when we applied the SIR from the complex model.

Hospital descriptors, aggregate patient characteristics, CO-CDI burden, and clinical testing practices significantly influence incidence of cHT-CDI. Benchmarking a cHT-CDI metric is feasible and should include facility and clinical variables.

Although the incidence of hospital-associated respiratory virus infection (HARVI) is well recognized, the risk factors for infection and impact on patient outcomes are not well characterized.

We identified a cohort of all inpatient admissions ≥24 hours duration at a single academic medical center from 2017 to 2020. HARVI were defined as respiratory virus detected in a test ordered after the 95th percentile of the virus-specific incubation period. Risk factors for HARVI were assessed using Cox proportional hazards models of the competing outcomes of HARVI and discharge. The associations between time-varying HARVI status and the rates of ICU admission, discharge, and in-hospital death were estimated using Cox-proportional hazards models in a competing risk framework.

HARVI incidences were 8.8 and 3.0 per 10,000 admission days for pediatric and adult patients, respectively. For adults, congestive heart failure, renal disease, and cancer increased HARVI risk independent of their associations with length of stay. HARVI risk was also elevated for patients admitted in September–June relative to July admissions. For pediatric patients, cardiovascular and respiratory conditions, cancer, medical device dependence, and admission in December increased HARVI risk. Lengths of stay were longer for adults with HARVI compared to those without, and hospital-associated influenza A was associated with increased risk of death. Rates of ICU admission were increased in the 5 days after HARVI identification for adult and pediatric patients. HARVI was not associated with length of stay or death among pediatric patients.

HARVI is associated chronic health conditions and increases morbidity and mortality.

Vancomycin is often initiated in hospitalized patients; however, it may be unnecessary or continued for longer durations than needed. Oversight of all vancomycin orders may not be feasible with widespread prescribing and strategies to enlist other clinicians to serve as stewards of vancomycin use are needed. We implemented 2 sequential interventions: a protocol in which the pharmacist orders MRSA nasal swab followed by a protocol requiring approval from pharmacists to continue vancomycin for >72 hours.

In this single-center, retrospective, quasi-experimental study, we evaluated vancomycin use after implementation of a pharmacy-driven MRSA nasal-swab ordering protocol and a vancomycin 72-hour restriction protocol. The primary outcome was the change in the standardized antibiotic administration ratio (SAAR) for antibacterial agents for resistant gram-positive infections. We also evaluated the impact on antibiotic utilization.

Following the MRSA swab protocol, the SAAR decreased from 1.26 to 1.13 (P < .001; 95% confidence interval [CI], 1.16–1.25). After the 72-hour approval process, the SAAR was 0.96 (P < .001; 95% CI, 1.0–1.12). Vancomycin utilization decreased from 138.9 to 125.3 days of therapy per 1,000 patient days following the MRSA swab protocol (P < .001) and to 112.7 (P < .001) following the 72-hour approval protocol. Interrupted time-series analysis identified a similar rate of decline in utilization following the 2 interventions (−0.3 and −0.5; P = .16). Both interventions combined resulted in a significant reduction (−1.5; P < .001).

Implementation of a pharmacist-driven MRSA nasal-swab ordering protocol, followed by a 72-hour approval protocol, was associated with a significant reduction in the SAAR for antibiotics used in the treatment of resistant gram-positive infections and a reduction in vancomycin utilization. Leveraging the oversight of primary service clinical pharmacists through these protocols proved to be an effective strategy.

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.

The gold standard for hand hygiene (HH) while wearing gloves requires removing gloves, performing HH, and donning new gloves between WHO moments. The novel strategy of applying alcohol-based hand rub (ABHR) directly to gloved hands might be effective and efficient.

A mixed-method, multicenter, 3-arm, randomized trial.

Adult and pediatric medical-surgical, intermediate, and intensive care units at 4 hospitals.

Healthcare personnel (HCP).

HCP were randomized to 3 groups: ABHR applied directly to gloved hands, the current standard, or usual care.

Gloved hands were sampled via direct imprint. Gold-standard and usual-care arms were compared with the ABHR intervention.

Bacteria were identified on gloved hands after 432 (67.4%) of 641 observations in the gold-standard arm versus 548 (82.8%) of 662 observations in the intervention arm (P < .01). HH required a mean of 14 seconds in the intervention and a mean of 28.7 seconds in the gold-standard arm (P < .01). Bacteria were identified on gloved hands after 133 (98.5%) of 135 observations in the usual-care arm versus 173 (76.6%) of 226 observations in the intervention arm (P < .01). Of 331 gloves tested 6 (1.8%) were found to have microperforations; all were identified in the intervention arm [6 (2.9%) of 205].

Compared with usual care, contamination of gloved hands was significantly reduced by applying ABHR directly to gloved hands but statistically higher than the gold standard. Given time savings and microbiological benefit over usual care and lack of feasibility of adhering to the gold standard, the Centers for Disease Control and Prevention and the World Health Organization should consider advising HCP to decontaminate gloved hands with ABHR when HH moments arise during single-patient encounters.

Trial Registration: NCT03445676.

We sought to determine whether increased antimicrobial use (AU) at the onset of the coronavirus disease 2019 (COVID-19) pandemic was driven by greater AU in COVID-19 patients only, or whether AU also increased in non–COVID-19 patients.

In this retrospective observational ecological study from 2019 to 2020, we stratified inpatients by COVID-19 status and determined relative percentage differences in median monthly AU in COVID-19 patients versus non–COVID-19 patients during the COVID-19 period (March–December 2020) and the pre–COVID-19 period (March–December 2019). We also determined relative percentage differences in median monthly AU in non–COVID-19 patients during the COVID-19 period versus the pre–COVID-19 period. Statistical significance was assessed using Wilcoxon signed-rank tests.

The study was conducted in 3 acute-care hospitals in Chicago, Illinois.

Hospitalized patients.

Facility-wide AU for broad-spectrum antibacterial agents predominantly used for hospital-onset infections was significantly greater in COVID-19 patients versus non–COVID-19 patients during the COVID-19 period (with relative increases of 73%, 66%, and 91% for hospitals A, B, and C, respectively), and during the pre–COVID-19 period (with relative increases of 52%, 64%, and 66% for hospitals A, B, and C, respectively). In contrast, facility-wide AU for all antibacterial agents was significantly lower in non–COVID-19 patients during the COVID-19 period versus the pre–COVID-19 period (with relative decreases of 8%, 7%, and 8% in hospitals A, B, and C, respectively).

AU for broad-spectrum antimicrobials was greater in COVID-19 patients compared to non–COVID-19 patients at the onset of the pandemic. AU for all antibacterial agents in non–COVID-19 patients decreased in the COVID-19 period compared to the pre–COVID-19 period.

Nursing home residents may be particularly vulnerable to coronavirus disease 2019 (COVID-19). Therefore, a question is when and how often nursing homes should test staff for COVID-19 and how this may change as severe acute respiratory coronavirus virus 2 (SARS-CoV-2) evolves.

We developed an agent-based model representing a typical nursing home, COVID-19 spread, and its health and economic outcomes to determine the clinical and economic value of various screening and isolation strategies and how it may change under various circumstances.

Under winter 2023–2024 SARS-CoV-2 omicron variant conditions, symptom-based antigen testing averted 4.5 COVID-19 cases compared to no testing, saving $191 in direct medical costs. Testing implementation costs far outweighed these savings, resulting in net costs of $990 from the Centers for Medicare & Medicaid Services perspective, $1,545 from the third-party payer perspective, and $57,155 from the societal perspective. Testing did not return sufficient positive health effects to make it cost-effective [$50,000 per quality-adjusted life-year (QALY) threshold], but it exceeded this threshold in ≥59% of simulation trials. Testing remained cost-ineffective when routinely testing staff and varying face mask compliance, vaccine efficacy, and booster coverage. However, all antigen testing strategies became cost-effective (≤$31,906 per QALY) or cost saving (saving ≤$18,372) when the severe outcome risk was ≥3 times higher than that of current omicron variants.

SARS-CoV-2 testing costs outweighed benefits under winter 2023–2024 conditions; however, testing became cost-effective with increasingly severe clinical outcomes. Cost-effectiveness can change as the epidemic evolves because it depends on clinical severity and other intervention use. Thus, nursing home administrators and policy makers should monitor and evaluate viral virulence and other interventions over time.