Prevalence of hospital-associated infections and its association with discharge destinations and hospital readmissions in Brussels, Belgium, from 2008 to 2020: A hospital-based, cross-sectional study

OBJECTIVES

To examine time trends of hospital-associated infections (HAIs) in people living in the Brussels-Capital Region, and to evaluate the consequences for hospitals and long-term care facilities (LTCFs).

DESIGN

Cross-sectional analyses of yearly hospital administrative data.

SETTING

All Belgian hospitals and discharge destinations, focusing on LTCFs.

PARTICIPANTS

All individuals from the Brussels-Capital Region hospitalized for >1 day throughout Belgium between 2008 and 2020 (N = 1,915,572).

METHODS

We calculated HAI prevalences and then, adjusting for confounders, the odds of being discharged to a LTCF or being readmitted within 30 days postdischarge after an HAI. HAIs included hospital-associated bloodstream infections, hospital-associated urinary tract infections, hospital-associated pneumonia, ventilator-associated pneumonia, and surgical-site infections.

RESULTS

Between 2008 and 2020, we identified 77,004 HAIs. Changes in time trends occurred. We observed a decrease of all HAIs from 2012 to 2014 from 5.17% to 2.19% (P < .001) and an increase from 2019 to 2020 from 3.38% to 4.06% (P < .001). Among patients with HAIs, 24.36% were discharged to LTCFs and 13.51% underwent early readmission. For stays ≥4 days, HAIs were associated with higher odds of LTCF discharge (adjusted odds ratio [aOR], 1.25; 95% confidence interval [CI], 1.22-1.28), but with lesser odds of early readmission (aOR, 0.88; 95% CI, 0.85-0.90).

CONCLUSIONS

Administrative data can be useful to detect HAIs trends, but they seem to underestimate the burden compared to surveillance systems. Risk factors of readmission should be identified during hospital stays to ensure continuity of care. Considering the results from 2020 coinciding with the COVID-19 pandemic, monitoring the impact of HAIs should continue.

Regional transmission patterns of carbapenemase-producing Enterobacterales: A healthcare network analysis

OBJECTIVE

Carbapenem-resistant Enterobacterales (CRE) pose a serious public health threat and spread rapidly between healthcare facilities (HCFs) during interfacility patient movement. We examined patterns of transmission of CRE associated with network clustering and positions during patient interfacility transfer.

METHODS

A retrospective cohort study was conducted in the Greater Houston region ofTexas, , and social network analysis was performed by constructing facility-to-facility patient transfer network using CRE surveillance data. The network method (community detection algorithm) was used to detect clustering patterns of CRE in the network. In addition, network measures of centrality and local connectivity (clustering coefficient) were computed for each healthcare facility. Zero-inflated negative binomial regression analysis was applied to test the association between network measures and facility-specific incidence rate of CRE.

RESULTS

A network of 268 healthcare facilities was identified, in which 10 acute-care hospitals (ACHs) alone accounted for 63% of identified CRE cases. Transmission of New Delhi metallo-β-lactamase-producing CRE occurred in 3 clusters, yet all cases were traced to patients who had had medical care abroad. The incidence rate of CRE attributed to ACHs was >4-fold (adjusted rate ratio, 4.5; 95% confidence interval [CI], 3.02-6.72) higher than that of long-term care facilities. Each additional patient shared with another HCF conferred a 3% (95% CI, 2%-4%) increase in the incidence rate of CRE at that HCF.

CONCLUSIONS

The incidence rates of CRE at a given HCF was predicted by the healthcare network metrics. Increased surveillance and selective targeting of high-risk facilities are warranted.

Evaluation of hospital readmissions for surgical site infections in Italy

Background

The objectives of this investigation are to assess the prevalence of hospital readmissions for surgical site infections (SSIs) in patients aged ≥18 in Italy and to describe the clinical characteristics of these patients and evaluate the possible association with readmission for SSIs.

Methods

A retrospective epidemiological study was conducted between January and May 2015 considering a sample of patients aged ≥18 years admitted to the surgical wards of two hospitals in Naples and undergoing surgery in the year 2014.

Results

3.8% of patients had been readmitted and 28.8% of them were readmitted to hospital due to SSIs. The multiple logistic regression model showed that readmissions for SSIs were significantly more common in smokers (odds ratio [OR] = 3.14; 95% confidence interval [CI] = 1.13-8.69), in patients with immunosuppression status (OR = 8.28; 95% CI = 1.76-38.87), in patients with low serum albumin (OR = 3.07; 95% CI = 1.05-9.01) and in patients who had undergone a surgical procedure classified as contaminated (OR = 10:44; 95% CI = 3.11-35.01) compared with those that had undergone a surgical procedure classified as clean.

Conclusions

The results point to the need that hospital infection prevention strategies are implemented in order to reduce morbidity and mortality for patients. Moreover, the measures taken to prevent infections would lead to a reduction in health spending since almost one third of readmissions to the hospital in our study were due to SSIs.

The Likelihood of Hospital Readmission Among Patients With Hospital-Onset Central Line-Associated Bloodstream Infections

OBJECTIVE

To determine whether central line-associated bloodstream infections (CLABSIs) increase the likelihood of readmission.

DESIGN

Retrospective matched cohort study for the years 2008-2009.

SETTING

Acute care hospitals.

PARTICIPANTS

Medicare recipients. CLABSI and readmission status were determined by linking National Healthcare Safety Network surveillance data to the Centers for Medicare and Medicaid Services' Medical Provider and Analysis Review in 8 states. Frequency matching was used on International Classification of Diseases, Ninth Revision, Clinical Modification procedure code category and intensive care unit status.

METHODS

We compared the rate of readmission among patients with and without CLABSI during an index hospitalization. Cox proportional hazard analysis was used to assess rate of readmission (the first hospitalization within 30 days after index discharge). Multivariate models included the following covariates: race, sex, length of index hospitalization stay, central line procedure code, Gagne comorbidity score, and individual chronic conditions.

RESULTS

Of the 8,097 patients, 2,260 were readmitted within 30 days (27.9%). The rate of first readmission was 7.1 events/person-year for CLABSI patients and 4.3 events/person-year for non-CLABSI patients (P<.001). The final model revealed a small but significant increase in the rate of 30-day readmissions for patients with a CLABSI compared with similar non-CLABSI patients. In the first readmission for CLABSI patients, we also observed an increase in diagnostic categories consistent with CLABSI, including septicemia and complications of a device.

CONCLUSIONS

Our analysis found a statistically significant association between CLABSI status and readmission, suggesting that CLABSI may have adverse health impact that extends beyond hospital discharge.