Journal of evaluation in clinical practice
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Visitation has a positive effect on patients and families, yet, it can disrupt intensive care unit (ICU) care and increase the risk of patient infections, which previously favoured face-to-face visits. The coronavirus disease 2019 (COVID-19) pandemic has raised the importance of virtual visits and led to their widespread adoption globally, there are still many implementation barriers that need to be improved. Therefore, this review aimed to explore the use of ICU virtual visit technology during the COVID-19 pandemic and the barriers and facilitators of virtual visits to improve virtual visits in ICUs. ⋯ This review identified key facilitating factors and barriers to ICU virtual visits, which can foster the development of infrastructure, virtual visiting workflows, guidelines, policies and visiting systems to improve ICU virtual visiting services. Further studies are necessary to identify potential solutions to the identified barriers.
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Review Meta Analysis
Clinical decision support systems in addiction and concurrent disorders: A systematic review and meta-analysis.
This review aims to synthesise the literature on the efficacy, evolution, and challenges of implementing Clincian Decision Support Systems (CDSS) in the realm of mental health, addiction, and concurrent disorders. ⋯ CDSS shows promise in mental health and addiction treatment but requires a nuanced approach for effective and ethical implementation. The results emphasise the need for continued research to ensure optimised and equitable use in healthcare settings.
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Reimbursement process of oncology drugs in Europe occurs within a complex decision-making process that varies between Member States. Distinctions between the States trigger societal debates since it is necessary to balance access to medicines and health systems sustainability. ⋯ There is a need for further research into key determinants of reimbursement decisions in Europe and the development of drug access models that can effectively address and overcome costs and effectiveness uncertainties.
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To investigate the factors affecting postoperative frailty and the relationship between frailty and postoperative recovery in patients undergoing cardiovascular surgery. ⋯ This study clarifies the role of frailty as an important factor influencing the recovery process in patients undergoing cardiovascular surgery. The findings show that frailty has a determining effect on postoperative recovery in these patients. Among the factors affecting frailty status, comorbidities, fear of postoperative falls, and postoperative general and psychological symptoms were found to contribute. These findings emphasise that these factors should be taken into account when assessing and managing the postoperative recovery process. Understanding these factors that influence postoperative frailty is crucial for patient care. Recognising the multifaceted nature of frailty, personalised interventions are needed to improve patient care and postoperative outcomes. Personalised interventions are particularly important for older women with multiple comorbidities, as they are more likely to be frail.
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Artificial Intelligence (AI) large language models (LLM) are tools capable of generating human-like text responses to user queries across topics. The use of these language models in various medical contexts is currently being studied. However, the performance and content quality of these language models have not been evaluated in specific medical fields. ⋯ Although LLMs provide parents with high-accuracy information about CKD, their use is limited compared with that of a reference source. The limitations in the performance of LLMs can lead to misinformation and potential misinterpretations. Therefore, patients and parents should exercise caution when using these models.