Clinical and economic burden of healthcare-associated infections: A prospective cohort study

Link to article at PubMed

PLoS One. 2023 Feb 23;18(2):e0282141. doi: 10.1371/journal.pone.0282141. eCollection 2023.


INTRODUCTION: Healthcare-associated infections (HAIs) have become a serious public health problem. Despite the fact that implementing evidence-based infection control strategies could prevent HAIs and save billions of dollars, Ethiopia lacks national surveillance studies on the rate, economic, and clinical burden of HAIs.

OBJECTIVE: To assess the clinical and economic burden of HAIs in hospitalized patients at Ayder comprehensive specialized hospital.

MATERIALS AND METHODS: A prospective cohort study design was conducted in patients with and without HAIs. A review of medical records, interviews, and patient bills was used to extract necessary information. The patients in the two arms were matched based on age, sex, Charlson comorbidity index, and ward type. Measurable factors were compared between infected and uninfected patients using the paired ttest or McNemar's test, as appropriate. Logistic regression was used to identify predictors of in-hospital mortality. Stata 14.1 was used to conduct all analyses.

RESULTS: A total of 408 patients, 204 with HAIs and 204 without HAIs were included in the study. In-hospital mortality was higher in patients with HAI (14.7% vs 7.8%, P = 0.028). Patients with HAI stayed an average of 8.3 days longer than controls (18.85 vs 10.59, P<0.001). The average direct medical costs for patients with HAI were 3033 Ethiopian birrs (ETB) higher than controls (4826 vs 1793, P<0.001). The presence of HAIs (AOR: 2.22, 95% CI: 1.13-4.39) and admission to intensive care units (AOR: 3.39, 95% CI: 1.55-7.40) were significant predictors of in-hospital mortality.

CONCLUSION: HAIs have a significant impact on in-hospital mortality, the length of extra hospital stays, and extra costs for medical care. Patients admitted to intensive care units and those with HAIs were found to be significant predictors of in-hospital mortality. Interventions must be implemented to prevent HAIs, especially in patients admitted to intensive care units.

PMID:36821590 | DOI:10.1371/journal.pone.0282141

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