Literature DB >> 32610246

Structure and process associated with the efficiency of intensive care units in low-resource settings: An analysis of the CHECKLIST-ICU trial database.

Leonardo S L Bastos1, Silvio Hamacher1, Fernando G Zampieri2, Alexandre B Cavalcanti3, Jorge I F Salluh4, Fernando A Bozza5.   

Abstract

PURPOSE: Characteristics of structure and process impact ICU performance and the outcomes of critically ill patients. We sought to identify organizational characteristics associated with efficient ICUs in low-resource settings.
MATERIALS AND METHODS: This is a secondary analysis of a multicenter cluster-randomized clinical trial in Brazil (CHECKLIST-ICU). Efficient units were defined by standardized mortality ratio (SMR) and standardized resource use (SRU) lower than the overall medians and non-efficient otherwise. We used a regularized logistic regression model to evaluate associations between organizational factors and efficiency.
RESULTS: From 118 ICUs (13,635 patients), 47 units were considered efficient and 71 non-efficient. Efficient units presented lower incidence rates (median[IQR]) of central line-associated bloodstream infections (4.95[0.00-22.0] vs 6.29[0.00-25.6], p = .04), utilization rates of mechanical ventilation (0.41[0.07-0.73] vs 0.58[0.19-0.82], p < .001), central venous catheter (0.67[0.15-0.98] vs 0.78[0.33-0.98], p = .04), and indwelling urinary catheter (0.62[0.22-0.95] vs 0.76[0.32-0.98], p < .01) than non-efficient units. The reported active surveillance of ventilator-associated pneumonia (OR = 1.72; 95%CI, 1.16-2.57) and utilization of central venous catheters (OR = 1.94; 95%CI, 1.32-2.94) were associated with efficient ICUs.
CONCLUSIONS: In low-resource settings, active surveillance of nosocomial infections and the utilization of invasive devices were associated with efficiency, supporting the management and evaluation of performance indicators as a starting point for improvement in ICU.
Copyright © 2020. Published by Elsevier Inc.

Entities:  

Keywords:  ICU benchmarking; ICU organization; Intensive care; Organizational characteristics; Quality indicators

Mesh:

Year:  2020        PMID: 32610246     DOI: 10.1016/j.jcrc.2020.06.008

Source DB:  PubMed          Journal:  J Crit Care        ISSN: 0883-9441            Impact factor:   3.425


  2 in total

1.  Characterisation of the first 250,000 hospital admissions for COVID-19 in Brazil: a retrospective analysis of nationwide data.

Authors:  Otavio T Ranzani; Leonardo S L Bastos; João Gabriel M Gelli; Janaina F Marchesi; Fernanda Baião; Silvio Hamacher; Fernando A Bozza
Journal:  Lancet Respir Med       Date:  2021-01-15       Impact factor: 30.700

2.  Using data envelopment analysis to perform benchmarking in intensive care units.

Authors:  Bianca B P Antunes; Leonardo S L Bastos; Silvio Hamacher; Fernando A Bozza
Journal:  PLoS One       Date:  2021-11-18       Impact factor: 3.240

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.