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. 2023 Mar 9;10(4):ofad129.
doi: 10.1093/ofid/ofad129. eCollection 2023 Apr.

A National Implementation Project to Prevent Healthcare-Associated Infections in Intensive Care Units: A Collaborative Initiative Using the Breakthrough Series Model

Paula Tuma  1   2 , Jose M Vieira Junior  3 , Elenara Ribas  4 , Karen C C D Silva  5 , Andrea K F Gushken  6 , Ethel M S Torelly  3 , Rafaela M de Moura  4 , Bruno M Tavares  5 , Cristiana M Prandini  6 , Paulo Borem  2 , Pedro Delgado  2 , Luciana Y Ue  7 , Claudia G de Barros  1 , Sebastian Vernal  5   6   1   4   3 ; Collaborative Study Group “Saúde em Nossas Mãos”
Collaborators, Affiliations

A National Implementation Project to Prevent Healthcare-Associated Infections in Intensive Care Units: A Collaborative Initiative Using the Breakthrough Series Model

Paula Tuma et al. Open Forum Infect Dis. .

Abstract

Background: Although there are simple and low-cost measures to prevent healthcare-associated infections (HAIs), they remain a major public health problem. Quality issues and a lack of knowledge about HAI control among healthcare professionals may contribute to this scenario. In this study, our aim is to present the implementation of a project to prevent HAIs in intensive care units (ICUs) using the quality improvement (QI) collaborative model Breakthrough Series (BTS).

Methods: A QI report was conducted to assess the results of a national project in Brazil between January 2018 and February 2020. A 1-year preintervention analysis was conducted to determine the incidence density baseline of the 3 main HAIs: central line-associated bloodstream infections (CLABSIs), ventilation-associated pneumonia (VAP), and catheter-associated urinary tract infections (CA-UTIs). The BTS methodology was applied during the intervention period to coach and empower healthcare professionals providing evidence-based, structured, systematic, and auditable methodologies and QI tools to improve patients' care outcomes.

Results: A total of 116 ICUs were included in this study. The 3 HAIs showed a significant decrease of 43.5%, 52.1%, and 65.8% for CLABSI, VAP, and CA-UTI, respectively. A total of 5140 infections were prevented. Adherence to bundles inversely correlated with the HAI incidence densities: CLABSI insertion and maintenance bundle (R = -0.50, P = .010 and R = -0.85, P < .001, respectively), VAP prevention bundle (R = -0.69, P < .001), and CA-UTI insertion and maintenance bundle (R = -0.82, P < .001 and R = -0.54, P = .004, respectively).

Conclusions: Descriptive data from the evaluation of this project show that the BTS methodology is a feasible and promising approach to preventing HAIs in critical care settings.

Keywords: central line-associated bloodstream infection; healthcare-associated infection; quality improvement; urinary tract infection; ventilator-associated pneumonia.

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Conflict of interest statement

Potential conflicts of interest. All authors: No reported conflicts of interest.

Figures

Figure 1.
Figure 1.
Adaptation of the Breakthrough Series model to the collaborative initiative “Large scale patient safety improvement” in Brazil. A, Act; D, Do; P, Plan; S, Study.
Figure 2.
Figure 2.
Summary of the main topics covered by the driver diagram of the Breakthrough Series model used in the collaborative initiative “Large scale patient safety improvement” in Brazil. CA-UTI, catheter-associated urinary tract infections; CLABSI, central line-associated bloodstream infections; HAI, healthcare-associated infections; ICU, intensive care unit; VAP, ventilation-associated pneumonia.
Figure 3.
Figure 3.
Shewhart charts between January 2018 and February 2020 and time-series modeling. (A) Incidence density of central line-associated bloodstream infections (CLABSI) per 1000 catheter-d. (B) Incidence density of ventilator-associated pneumonia (VAP) per 1000 ventilator-d. (C) Incidence density of catheter-associated urinary tract infections (CA-UTI) per 1000 catheter-d. (D) Incidence density of CLABSI time-series model. (E) Incidence density of VAP time-series model. (F) Incidence density of CA-UTI time-series model. Blue dots, monthly incidence density; green line, center line; red line, upper and lower control limits. ICU, intensive care unit; IPCSL1, incidence density of central line-associated bloodstream infections; ITU-AC1, incidence density of catheter-associated urinary tract infections; PAV1, incidence density of ventilation-associated pneumonia;
Figure 4.
Figure 4.
Correlation between adhesion to the insertion/maintenance bundles and the incidence densities of the studied healthcare-associated infections. (A) Correlation between adhesion to the insertion bundle and incidence density of central line-associated bloodstream infections per 1000 catheter-d. (B) Correlation between adhesion to the maintenance bundle and incidence density of central line-associated bloodstream infections per 1000 catheter-d. (C) Correlation between adhesion to the prevention bundle and incidence density of ventilator-associated pneumonia per 1000 ventilator-d. (D) Correlation between adhesion to the insertion bundle and incidence density of catheter-associated urinary tract infections per 1000 catheter-d. (E) Correlation between adhesion to the maintenance bundle and incidence density of catheter-associated urinary tract infections per 1000 catheter-d. IPCSL1, incidence density of central line-associated bloodstream infections; IPCSL3, adherence to the insertion bundle central line-associated bloodstream infections; IPCSL4, adherence to the maintenance bundle central line-associated bloodstream infections; ITU-AC1, incidence density of catheter-associated urinary tract infections; ITU-AC3, adherence to the insertion bundle catheter-associated urinary tract infections; ITU-AC4, adherence to the maintenance bundle catheter-associated urinary tract infections; PAV1, incidence density of ventilation-associated pneumonia; PAV3, adherence to the prevention bundle ventilation-associated pneumonia.
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