Hospital Context Determinants of Variability in Healthcare-Associated Infection Prevalence: Multi-Level Analysis

Healthcare-associated infections (HAIs) represent a major challenge in patient safety that affects services disproportionally. This paper aimed to assess how the HAI prevalence varies between hospital services and what contextual characteristics may explain such variance. A cross-sectional study was conducted on adult patients in Portuguese hospitals, using data from the European point prevalence survey of HAI prevalence. The study variables included patient, structural, and process variables, tested as risk factors, with patients clustered in hospitals. Variables with a <i>p</i>-value ≤ 0.2 in univariate analyses were retested in a multivariable model. A total of 18,261 patients from 119 hospitals were included: 736 from 56 intensive care units (ICUs), 3160 from 72 surgical departments, and 8081 from 90 medical departments. The HAI prevalence was 7.9%, 5.9%, and 1.7%, respectively. In ICUs, only the number of devices was associated with the HAI prevalence. In surgical departments, age, comorbidities, being a specialized hospital, and a higher ratio of infection prevention and control (IPC) personnel were associated with higher SSI. The safety climate was associated with lower SSI. In medical departments, age and devices were positively associated, whereas a larger ratio of IPC nurses was negatively associated. These results may help implement targeted interventions to achieve optimal results in each department.

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Publication Details

Journal
Microorganisms
Published
2024-12-07
DOI
https://doi.org/10.3390/microorganisms12122522
Citations
3
Primary Topic
Infection Control in Healthcare
Type
article
Field-Weighted Citation Impact
1.17
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article

Hospital Context Determinants of Variability in Healthcare-Associated Infection Prevalence: Multi-Level Analysis

José Artur Paiva, Ana Fareleira, Ana Lebre, Rui Malheiro et al.
3 citations
Microorganisms
Infection Control in Healthcare
1.17
article

Hospital Context Determinants of Variability in Healthcare-Associated Infection Prevalence: Multi-Level Analysis

José Artur Paiva, Ana Fareleira, Ana Lebre, Rui Malheiro, João Gonçalves-Pereira, Dulce Pascoalinho, Rita Sá-Machado, André Gomes, Carlos Fernandes
article en
3 citations

Abstract

Healthcare-associated infections (HAIs) represent a major challenge in patient safety that affects services disproportionally. This paper aimed to assess how the HAI prevalence varies between hospital services and what contextual characteristics may explain such variance. A cross-sectional study was conducted on adult patients in Portuguese hospitals, using data from the European point prevalence survey of HAI prevalence. The study variables included patient, structural, and process variables, tested as risk factors, with patients clustered in hospitals. Variables with a <i>p</i>-value ≤ 0.2 in univariate analyses were retested in a multivariable model. A total of 18,261 patients from 119 hospitals were included: 736 from 56 intensive care units (ICUs), 3160 from 72 surgical departments, and 8081 from 90 medical departments. The HAI prevalence was 7.9%, 5.9%, and 1.7%, respectively. In ICUs, only the number of devices was associated with the HAI prevalence. In surgical departments, age, comorbidities, being a specialized hospital, and a higher ratio of infection prevention and control (IPC) personnel were associated with higher SSI. The safety climate was associated with lower SSI. In medical departments, age and devices were positively associated, whereas a larger ratio of IPC nurses was negatively associated. These results may help implement targeted interventions to achieve optimal results in each department.

MicroorganismsVol. 12(12)
University of Lisbon (PT), Universidade do Porto (PT), Hospital de São João (PT), Administração Regional de Saúde de Lisboa e Vale do Tejo (PT), IPO Porto (PT), CUF Porto Hospital (PT), PT Inovação e Sistemas (Portugal) (PT), Direção Geral do Território (PT)
Climate action
Openalex Percentile: Top 20%
Infection Control in Healthcare
1.17
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