Journal of evaluation in clinical practice
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Clinical abbreviations pose a challenge for clinical decision support systems due to their ambiguity. Additionally, clinical datasets often suffer from class imbalance, hindering the classification of such data. This imbalance leads to classifiers with low accuracy and high error rates. Traditional feature-engineered models struggle with this task, and class imbalance is a known factor that reduces the performance of neural network techniques. ⋯ Deep neural network methods, particularly Bi-LSTM, offer promising alternatives to traditional feature-engineered models for clinical abbreviation disambiguation. By employing data generation techniques, we can address the challenges posed by limited-resource and imbalanced clinical datasets. This approach leads to a significant improvement in model accuracy for clinical abbreviation disambiguation tasks.
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Electronic health records (EHR) are frequently used for epidemiological research including drug utilisation studies in a defined population such as the population with knee osteoarthritis (KOA). We sought to describe the process of defining a cohort of patients with KOA from a large UK primary care database and estimate the annual incidence of diagnosed KOA between 2000 and 2015. ⋯ This study logically/sensibly defined a cohort of patients with diagnosed KOA through the application of several strategies. This was an essential step to avoid subsequent over or underestimation of the prevalence of drug utilisation and the associated adverse clinical outcomes within primary care patients with KAO.
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This paper explores how frontline nurses experienced the onset of the coronavirus disease (COVID-19) pandemic to provide appropriate care during a global health crisis. ⋯ Understanding the challenges faced by frontline nurses during the onset of the COVID-19 pandemic may help healthcare practitioners and policy makers to implement targeted interventions, support mechanisms and resource allocation strategies that enhance the well-being of frontline nurses and optimise patient care delivery during health crises.
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The National Health Service (NHS) Long Term Plan was published in January 2019. One of its objectives was restructuring outpatient services, as part of an Outpatient Transformation initiative. Monitoring of trusts' adherence to the objectives of the Long Term Plan is therefore required to benchmark progress against national objectives. ⋯ There are deficiencies in current outpatient establishments that may hinder the achievement of objectives set in the NHS Long Term Plan. Changes at all levels of healthcare are required, with increased reliance on technologies and investment in support for transformation management.