Conectar
To identify facilitators and barriers to quality, equitable discharge teaching by paediatric emergency department nurses during the COVID-19 pandemic, describe impacts of inequitable discharge teaching, and identify potential solutions to the barriers.
Twenty-two nurses in a single urban paediatric hospital participated in individual interviews from January to April 2022 via phone or videoconference. Interviews were transcribed and analysed using an inductive codebook.
Six barriers to equitable discharge teaching were identified: ED overcrowding, travel nurse training/knowledge, burnout and stress, increased role complexity, COVID precautions, and resource bottlenecks. Two facilitators were also identified: engagement and effective communication. Nurses described the impacts of these barriers along with proposed solutions to improve discharge teaching.
The COVID-19 pandemic created additional barriers to discharge teaching in the paediatric emergency department. Nurses identified barriers and facilitators, the impacts on patients and families, and potential solutions to improve equitable discharge teaching.
This study identifies how periods of high patient volumes or frequent process changes during a pandemic exacerbate inequities in discharge teaching.
This study identifies barriers and facilitators that shaped nurses' ability to provide quality, equitable discharge teaching during the COVID-19 pandemic and offers actionable guidance for hospital leaders and health systems to improve discharge teaching and enhance emergency preparedness for future public health crises.
This study conforms to the Standards for Reporting Qualitative Research.
This study did not include patient or public involvement in its design, conduct, or reporting.
ClinicalTrials.gov identifier: NCT04676490
High costs of screening and diagnostic tests remain a major barrier to timely tuberculosis (TB) identification in resource-limited settings. Evidence on the cost-effectiveness of scalable screening algorithms is limited. Start4All is a research project aimed at developing and evaluating algorithmic approaches to TB screening and diagnosis, with the goal of optimising technical and allocative efficiency when expanding diagnostic coverage to primary healthcare and community settings.
Five screening and diagnostic tests will be evaluated: a capillary blood-based assay (C-reactive protein (CRP)), sputum-based rapid molecular tests (PCR; individual and pooled Xpert MTB/RIF Ultra assay (Xpert Ultra, Cepheid®, California, USA)), a lateral-flow urine-based test for lipoarabinomannan (LF-LAM), and digital chest X-rays with artificial intelligence-based computer-aided detection (CXR-CAD). A microbiological reference standard of positive culture using the mycobacteria growth indicator tube will be used to confirm TB disease.
We will compare the cost and effectiveness of concurrent and sequential positive serial combinations (screening algorithms) of CRP, CXR-CAD, LF-LAM, individual and pooled Xpert Ultra. Diagnostic performance will be estimated using sensitivity, specificity, predictive values and proportions of positive results, with Bayesian inference used to derive these estimates. The analysis will include adults (15 years and older) only and will be stratified by HIV status and level of care, including facility and community-based case finding. Effectiveness will be assessed based on the number of people with TB detected. Cost analysis will be conducted from the provider perspective, incorporating commodity and implementation costs. A decision tree model will be developed to assess the cost per number of persons with confirmed TB detected across all countries. Probabilistic sensitivity analysis will be conducted to account for uncertainty in model parameters, incorporating willingness-to-pay and willingness-to-accept thresholds.
WHO ethical review committee approval ERC.0003921. Data will be available on reasonable request to the principal investigator of the consortium.
FreshRSS 