Journal of evaluation in clinical practice
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The present paper aimed at discussing how the process of decision-making should be taken care of in healthcare services. ⋯ In depht analysis of meaning-making processes is crucial for better refining good practices of shared decision-making.
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Healthcare systems remain disease oriented despite growing sustainability concerns caused by inadequate management of patients with multimorbidity. Comprehensive care programmes (CCPs) can play an important role in streamlining care delivery, but large differences in setup and results hinder firm conclusions on their effectiveness. Many elements for successful implementation of CCPs are identified, but strategies to overcome barriers and embed programmes within health systems remain unknown. ⋯ The introduction of a CCP is feasible, and exploratory analysis on effectiveness shows lower hospital care use without decreasing patient satisfaction. However, this is accompanied by several challenges that show current fragmented systems still do not support implementation of integrated care initiatives. Overcoming those comes with substantial costs and may require a strong bottom-up implementation within a motivated team and actions on all levels of healthcare systems.
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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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Patient navigation is a recommended practice to improve cancer screenings among underserved populations including those residing in rural areas with care access barriers. We report on patient navigation programme adaptations to increase follow-up colonoscopy rates after abnormal fecal testing in rural primary care practices. ⋯ While unplanned adaptations were implemented to address the contextual impact of the COVID-19 pandemic on care access patterns and staffing, the changes to training content and context were beneficial to the rural setting overall and should be sustained. Our findings can guide future efforts to optimise the success of such programmes in other rural settings and highlight the important role of adaptations in implementation projects.