RESUMEN
INTRODUCTION: Patients undergoing intubation and mechanical ventilation in an intensive care unit risk developing post-extubation oropharyngeal dysphagia (PED). PED can lead to aspiration complications, aspiration pneumonia, and prolonged hospitalization, as well as increased repeat intubation and in-hospital morbidity and mortality. OBJECTIVE: This evidence implementation project aimed to promote evidence-based screening and early detection of PED in an adult intensive care unit in a secondary public hospital in Brazil. METHOD: The project followed the seven-phase JBI Evidence Implementation Framework to promote changes at the study site. The JBI Practical Application of Clinical Evidence System (PACES) and Getting Research into Practice (GRiP) approach were also used. The project was developed considering the main barriers to best practices, which were identified through a baseline audit. An educational program was designed to address the identified barriers. Two follow-up audits were then conducted to assess the changes in compliance with the evidence-based practices. RESULTS: The baseline audit showed deficits in current practices. The first follow-up audit indicated improved compliance with best practices, with five of the seven audit criteria showing 100% compliance. The second follow-up audit indicated that compliance remained at 100% for those five criteria and increased for the other two after an additional intervention to address poor results in nursing care documentation. CONCLUSION: The first follow-up audit showed good adherence to the educational program for the screening and detection of PED by nurses. The second follow-up audit, in line with the new strategies, showed improvement in nursing documentation. SPANISH ABSTRACT: http://links.lww.com/IJEBH/A241.
RESUMEN
Decision support systems (DSSs) are recognized as important tools, capable of processing high volumes of data and increasing productivity. The usability of these tools affects their effectiveness. By evaluating the interactions between registered nurses (RNs) and the DSSs, this study explores how they impact RN decision-making. This study analyzed 24 months (2011-2012) of data collected in Brazil in two units of a large, public, urban hospital in São Paulo that uses a nurse documentation system with an embedded DSS based on NANDA-I. Using mixed effects logistic regression, this study analyzed the agreement between RNs and a DSS when selecting nursing diagnoses. Results suggest that the agreement is mediated by characteristics of the RNs (education and experience) as well as units and year of encounter. Surprisingly, disagreement between RN and DSS when selecting defining characteristics (DC) had positive effects on the odds of agreement on diagnoses. Our results suggest that DSSs support nurses' clinical decision making, but the nurse's clinical judgment is the mediating factor. More research is necessary.