Journal of evaluation in clinical practice
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Artificial intelligence (AI) has significant transformative potential across various sectors, particularly in health care. This study aims to develop a protocol for the content analysis of a method designed to assess AI applications in drug-related information, specifically focusing on contraindications, adverse reactions, and drug interactions. By addressing existing challenges, this preliminary research seeks to enhance the safe and reliable integration of AI into healthcare practices. ⋯ This preliminary study demonstrates the potential for using an AI-powered tool to standardize drug-related information retrieval, particularly for contraindications and adverse reactions. While AI responses were generally appropriate, improvements are needed in identifying contraindicated drug interactions. Further research with larger datasets and broader evaluations is required to enhance AI's reliability in healthcare settings.
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This study aims to evaluate the workload of clinical nurses by measuring the work relative value (work RVU) of common nursing items based on the resource-based relative value scale in China. ⋯ We have adhered to relevant EQUATOR guidelines and named the reporting method.
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Developing a feasible and sensitive evaluation strategy for a new mental health service is a challenge that requires consideration of what a service is trying to achieve and what a 'good' outcome might look like. Perinatal mental illnesses are complex in their causes and treatment. Mother Baby Units provide specialist perinatal mental health care to parents experiencing mental illness in the perinatal period, with evaluations demonstrating clinical and social outcomes. There has however been remarkably little research on how MBUs achieve these outcomes. ⋯ Articulating the approach to evaluation provides a contribution to evaluation knowledge for others evaluating complex public health interventions. The relational nature of perinatal mental health experiences challenges individualistic approaches to care delivery, funding and evaluation. As part of service establishment, there is a need to consider what a 'good' outcome of care might be and to develop evaluation approaches that capture the relational components of recovery as well as the factors that support families to sustain change.