Resilience of the healthcare system has been described as the ability to absorb, adapt, and respond to stress while maintaining the provision of safe patient care. We quantified the impact that stressors associated with the COVID-19 pandemic had on patient safety, as measured by central line-associated bloodstream infections (CLABSIs) reported to the Centers for Disease Control and Prevention’s National Healthcare Safety Network.

Acute care hospitals were mandated to report markers of resource availability (staffing and hospital occupancy with COVID-19 inpatients) to the federal government between July 2020 and June 2021. These data were used with community levels of COVID-19 to develop a statistical model to assess factors influencing rates of CLABSIs among inpatients during the pandemic.

After risk adjustment for hospital characteristics, measured stressors were associated with increased CLABSIs. Staff shortages for more than 10% of days per month were associated with a statistically significant increase of 2 CLABSIs per 10,000 central line days versus hospitals reporting staff shortages of less than 10% of days per month. CLABSIs increased with a higher inpatient COVID-19 occupancy rate; when COVID-19 occupancy was 20% or more, there were 5 more CLABSIs per 10,000 central line days versus the referent (less than 5%).

Reporting of data pertaining to hospital operations during the COVID-19 pandemic afforded an opportunity to evaluate resilience of US hospitals. We demonstrate how the stressors of staffing shortages and high numbers of patients with COVID-19 negatively impacted patient safety, demonstrating poor resilience. Understanding stress in hospitals may allow for the development of policies that support resilience and drive safe care.

Central line-associated bloodstream infections (CLABSIs) result in morbidity and mortality among hospitalized patients. Hospital interventions to reduce the incidence of CLABSI are often broadly applied to all patients with central venous access. Identifying central lines at high risk for CLABSI at time of insertion will allow for a more focused delivery of preventative interventions.

This was an observational cohort study conducted at three hospitals including all patients who received central venous access. CLABSIs were identified using an institutional CLABSI database maintained by the hospital epidemiology team. Logistic regression (LASSO) and machine learning (random forest, XGboost) techniques were applied for the prediction of CLABSI occurrence, adjusting for selected patent and insertion-level characteristics.

A total of 40,008 central venous catheters were included, of which 409 (1.02%) were associated with CLABSI. The random forest and the XGBoost models had the highest discrimination (Area Under the Received Operating Curve [AUC] 0.79) followed by LASSO (0.73). High illness severity, receipt of total parenteral nutrition, receipt of hemodialysis, pre-insertion hospital length-of-stay, and low albumin levels were all predictive of CLABSI occurrence. Precision for all models was poor owing to a high false-positive rate.

CLABSI can be predicted based upon patient and insertion level factors in the electronic health record. In this study, random forest and gradient-boosted models had the highest AUC. Prediction cut-offs for the identification of CLABSI can be adjusted based upon the acceptable rate of false-positives for a given CLABSI preventative intervention.

To compare the risk and exposure-adjusted central line-associated bloodstream infection (CLABSI) rates between racial and ethnic groups.

Retrospective cohort study.

15 network hospitals in Illinois and Michigan (Part of OSF HealthCare).

Patients of all age groups who had a central line inserted and removed during the same hospitalization between 01/2018 and 06/2023.

CLABSI rates/1000 Central line days of the four major racial and ethnic categories (Hispanic, non-Hispanic White [NHW], non-Hispanic Black [NHB], and non-Hispanic others) were analyzed by generalized Poisson regression. Confounding variables included in the regression model based on a directed acyclic graph and included age group, insurance class, language, ICU admission, diagnostic cohorts (obesity, diabetes, dialysis, cancer, neutropenia), and line usage (blood products, chemotherapy, total parenteral nutrition).

27,674 central lines (244,889 catheter days) on 23,133 unique patients (median age 64 years, 8% pediatric patients) were included in the analysis. Overall, the CLABSI rate was 1.070/1000 Central line days. 76% of the study population was NHW, 17% NHB, and 4% Hispanic. After adjusting for confounding variables, Hispanic patients had higher CLABSI rates than NHW (IRR 1.89, 95% CI 1.15–3.10, P = .013). No significant difference was observed in the CLABSI rates between NHW and NHB patients.

Disparities in hospital-associated conditions persist even after controlling for patient-level risk factors and exposures, with Hispanic patients at the highest risk.

Cases of hospital-onset bacteremia and fungemia (HOBF) are on the rise in Japanese hospitals, but little is known about their incidence in hospitals and how it relates to the availability of services provided by infectious diseases departments.

We herein investigated the monthly incidence density of HOBF per 1,000 patient days from 2013 through 2023 at a tertiary care hospital in Japan. The incidence of overall HOBF and pathogen-specific HOBF, including those caused by Enterobacterales, Staphylococcus aureus, coagulase-negative staphylococci (CNS), and Candida species, was tracked. Changes in the HOBF trend before and after the establishment of an infectious diseases department at the hospital were evaluated.

In total, 4,315 HOBF-related events were identified. The overall incidence density of HOBF increased by 2.4-fold from 0.58 per 1,000 PD in 2013 to 1.42 per 1,000 PD in 2023. Both the level and trend changes in the incidence density of overall HOBF (+0.3142 for change in level [P < .001]; +0.0085 for change in trend [P < .001]), HOBF caused by S. aureus (+0.0983 for change in level [P < .001]; +0.0016 for change in trend [P = 0.016]), and Candida spp. (+0.0466 for change in level [P = 0.030]; +0.0019 for change in trend [P = 0.002]) significantly increased after the establishment of the infectious diseases department.

The incidence density of overall HOBF and clinically important pathogen-specific HOBF increased over the last decade. The availability of services through the infectious diseases department was significantly associated with an increase in the HOBF incidence, likely suggesting improvement in the diagnosis of HOBF.

To quantify the impact of patient- and unit-level risk adjustment on infant hospital-onset bacteremia (HOB) standardized infection ratio (SIR) ranking.

A retrospective, multicenter cohort study.

Infants admitted to 284 neonatal intensive care units (NICUs) in the United States between 2016 and 2021.

Expected HOB rates and SIRs were calculated using four adjustment strategies: birthweight (model 1), birthweight and postnatal age (model 2), birthweight and NICU complexity (model 3), and birthweight, postnatal age, and NICU complexity (model 4). Sites were ranked according to the unadjusted HOB rate, and these rankings were compared to rankings based on the four adjusted SIR models.

Compared to unadjusted HOB rate ranking (smallest to largest), the number and proportion of NICUs that left the fourth quartile (worst-performing) following adjustments were as follows: adjusted for birthweight (16, 22.5%), birthweight and postnatal age (19, 26.8%), birthweight and NICU complexity (22, 31.0%), birthweight, postnatal age and NICU complexity (23, 32.4%). Comparing NICUs that moved into the better-performing quartiles after birthweight adjustment to those that remained in the better-performing quartiles regardless of adjustment, the median percentage of low birthweight infants was 17.1% (Interquartile Range (IQR): 15.8, 19.2) vs 8.7% (IQR: 4.8, 12.6); and the median percentage of infants who died was 2.2% (IQR: 1.8, 3.1) vs 0.5% (IQR: 0.01, 12.0), respectively.

Adjusting for patient and unit-level complexity moved one-third of NICUs in the worst-performing quartile into a better-performing quartile. Risk adjustment may allow for a more accurate comparison across units with varying levels of patient acuity and complexity.

We introduced a urinary tract infection (UTI) panel requiring symptom documentation and identification of special populations linked to reflex urine culturing and evaluated its impact on catheter-associated UTI (CAUTI) including during the COVID-19 pandemic.

Quasi-experimental encompassing 3 periods: pre-panel (January 2014–March 2015), post-panel (April 2015–March 2020), and post-panel COVID (April 2020–June 2022).

Tertiary care center inpatients.

Poisson regression and interrupted time series (ITS) analysis evaluated changes in catheter days (CD), urine cultures (UC), and CAUTI measured by 1,000 CD and patient days (PD). National Health Safety Network standardized infection ratio (SIR) and standardized utilization ratio (SUR) data were analyzed.

UC per 1,000 PD decreased after implementation (pre-panel 36.9 vs 16.6 post-panel vs 14.4 post-panel COVID, all P < .001). CD declined pre-panel versus post-panel (RR 0.37, P < .001) but not from post-panel to post-panel COVID (RR 0.94, P = .88). UTI panel implementation was associated with a 40% decrease in CAUTI rates per 1,000 CD (P < .001). During the COVID-19 pandemic (post-panel COVID), a nonsignificant increase of 13% (P = .61) in CAUTI was noted but remained 32% lower than pre-panel (P = .02). The slope of change using ITS changed from negative to positive but was nonsignificant (P = .26). CAUTI rates per 1,000 PD demonstrated greater reductions (pre- vs post-panel (RR 0.37; 95% CI, 0.29–0.47) and pre- vs post-panel COVID (RR 0.35; 95% CI, 0.26–0.46)). SIRs were unavailable before 2016, but median SIRs post-panel compared to post-panel COVID were similar (1.05 vs 1.56, respectively, P = .067).

Implementation of the UTI panel was associated with a reduction in both UC and CAUTI with the impact maintained despite the COVID-19 pandemic.

To identify risk factors for methicillin-susceptible (MSSA) and methicillin-resistant S. aureus (MRSA) nasal carriage and surgical site infection (SSI) among patients undergoing fracture fixation procedures who were included in a quality improvement protocol involving screening patients for S. aureus nasal carriage and treating carriers with intranasal mupirocin and chlorhexidine bathing.

Retrospective cohort study.

Level 1 trauma center.

1,254 adults who underwent operative fixation of 1,298 extremity or pelvis fractures between 8/1/2014 – 7/31/2017.

We calculated rates of S. aureus nasal carriage and SSI. We used multivariable stepwise logistic regression and selected the final models based on Akaike information criterion.

Of the 1,040 screened first procedures, 262 (25.19%) were performed on S. aureus nasal carriers: 211 (20.29%) on MSSA carriers and 51 (4.90%) on MRSA carriers. Long-term care facility residence (odds ratio [OR] 3.38; 95% confidence interval [CI] 1.17–9.76) was associated with MRSA nasal carriage. After adjusting for statistically and clinically significant variables, MRSA carriage was significantly associated with any SSI (OR 4.58; 95% CI 1.63–12.88), S. aureus SSI (OR 10.11; 95% CI 3.25–31.42), and MRSA SSI (OR 27.25; 95% CI 5.33–139.24), whereas MSSA carriage was not. Among S. aureus carriers, any chlorhexidine use was documented for 232 (88.55%), and any intranasal mupirocin was documented for 85 (40.28%) MSSA carriers and 33 (64.71%) MRSA carriers.

MRSA carriage was associated with a significant risk of SSI after operative fracture fixation. Many carriers did not undergo decolonization, suggesting that a simplified decolonization protocol is needed.

To evaluate the hospital-reported cost of care, clinical burden, and incidence of hospital-onset bacteremia and fungemia (HOB) for hospital admissions with surgical site infections (SSI).

A cross-sectional study of 38 acute-care hospital admissions with a procedure under the National Healthcare Safety Network (NHSN) surveillance for SSI was conducted. SSI admissions were identified through NHSN reporting by the hospital. Clinical outcomes were estimated for SSI compared to no SSI controls using propensity matching and multivariable adjusted models that controlled for patient and hospital demographics; these endpoints were also compared for SSI admissions with and without HOB co-occurrence.

The rate of hospital-reported SSI was 0.15 per 100 admissions with a procedure under surveillance for SSI. Admissions with SSI compared to no SSI had significantly higher incremental hospital-reported cost of $30,689 and length of stay (LOS) was 11.6 days higher. The incidence of HOB was 6-fold higher in admissions with SSI compared to no SSI. For SSI admissions with HOB vs. no HOB, HOB added $28,049 to cost of care and 6.5 days to the LOS.

Hospital-reported SSIs were associated with higher clinical and economic burden. Patients with SSI and HOB had even more deleterious outcomes. These data may inform programs to augment infection prevention bundles targeting SSIs and downstream complications or comorbidities like HOB.

Validate a public health model identifying patients at high risk for carbapenem-resistant Enterobacterales (CRE) on admission and evaluate performance across a healthcare network.

Retrospective case-control studies

Adults hospitalized with a clinical CRE culture within 3 days of admission (cases) and those hospitalized without a CRE culture (controls).

Using public health data from Atlanta, GA (1/1/2016–9/1/2019), we validated a CRE prediction model created in Chicago. We then closely replicated this model using clinical data from a healthcare network in Atlanta (1/1/2015–12/31/2021) (“Public Health Model”) and optimized performance by adding variables from the healthcare system (“Healthcare System Model”). We frequency-matched cases and controls based on year and facility. We evaluated model performance in validation datasets using area under the curve (AUC).

Using public health data, we matched 181 cases to 764,408 controls, and the Chicago model performed well (AUC 0.85). Using clinical data, we matched 91 cases to 384,013 controls. The Public Health Model included age, prior infection diagnosis, number of and mean length of stays in acute care hospitalizations (ACH) in the prior year. The final Healthcare System Model added Elixhauser score, antibiotic days of therapy in prior year, diabetes, admission to the intensive care unit in prior year and removed prior number of ACH. The AUC increased from 0.68 to 0.73.

A CRE risk prediction model using prior healthcare exposures performed well in a geographically distinct area and in an academic healthcare network. Adding variables from healthcare networks improved model performance.

To enumerate and describe the effect of whole genome sequencing (WGS) on epidemiological investigations of healthcare-associated transmission of nontuberculous mycobacteria (NTM).

Systematic review.

We performed a literature search using targeted search terms to identify articles meeting inclusion criteria. Data extraction of study characteristics and outcomes was performed by two independent researchers. The primary outcome was the author interpretation of WGS utility in the investigation of suspected healthcare-associated transmission of NTM. The secondary outcome was whether a transmission route was identified through WGS.

Thirty-one studies were included in the final analysis with 28 (90%) concluding that WGS was helpful in transmission investigations and in 19 of these 28 (68%) WGS aided in identifying a transmission route. The most common identified transmission routes were water-borne point sources (10), heater-cooler units (6), patient-to-patient (4), and a healthcare worker (1).

WGS is an informative tool in investigating healthcare transmission of NTM.

Antimicrobial resistance is increased by antibiotic overuse, so it’s crucial for stewardship programs to monitor and control their use. Pneumonia, particularly prevalent among older adults in Japan, is requiring higher rates of medical treatment. This study aimed to develop an improved method for benchmarking broad-spectrum antibiotic use in the empiric treatment of pneumonia in older adult inpatients by applying the “smoothed” observed-to-expected (O/E) ratio which adjusts for hospital-level variations and minimizes the effect of extreme values.

Using nationwide data from the Diagnosis Procedure Combination research group, pneumonia patients between April 1st 2018 and March 31st 2020 were analyzed. The primary outcome was the smoothed O/E ratio of the broad-spectrum antibiotic use for hospitals. It was calculated from the predicted values of broad-spectrum antibiotic use that were obtained through multilevel logistic regression using patient characteristics as predictors from data clustered by hospitals. The analysis investigated the risk-adjusted use of broad-spectrum antibiotics among hospitals.

A total of 244,747 patients from 958 hospitals were included, with a mean age of 81 (±8.30) years. The proportion of broad-spectrum antibiotic use was 35.3% (n = 86,316). The prediction model showed a C-statistic of 0.722. There was a noticeable variation in the O/E ratio among hospitals with values ranging from 0.13 (95% CI: 0.09–0.20) to 2.81 (95% CI: 2.64–2.97).

Using a risk-adjusted smoothed O/E ratio, we assessed the use of broad-spectrum antibiotics across hospitals, identifying those with high O/E ratios that may indicate a need for improvement.

Concerns about penicillin-cephalosporin cross-reactivity have historically led to conservative prescribing and avoidance of cephalosporins in patients with penicillin allergy labels, potentially causing suboptimal outcomes. Recent evidence suggests a lower risk of cross-reactivity, prompting a reassessment of alert systems.

To assess the impact of limited penicillin cross-reactivity alerts on outpatient cephalosporin use and the incidence of adverse reactions in a healthcare setting.

This retrospective cohort study compared cephalosporin prescribing and adverse reactions in patients labeled as penicillin-allergic before and after limiting penicillin cross-reactivity alerts in the electronic medical record at a large academic medical center.

Among 17,174 patients (8,131 pre- and 9,043 post-implementation), there was a statistically significant increase in outpatient cephalosporin prescribing by 8% (P < .001). The use of alternative antibiotic classes decreased. There was no statistically significant increase in adverse events pre- and post-implementation (0.036%–0.058%, P = .547), and no severe events were attributable to cross-reactivity. The alert modification reduced alerts by 92% (P < .001).

The reduction of penicillin-cephalosporin cross-reactivity alerts was associated with increased cephalosporin use, without a significant increase in adverse reactions. This demonstrates that the practice is safe and decreases alert burden.