Academic emergency medicine : official journal of the Society for Academic Emergency Medicine
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Review Meta Analysis
Interventions to improve emergency department throughput and care delivery indicators: A systematic review and meta-analysis.
Emergency department (ED) crowding has repercussions on acute care, contributing to prolonged wait times, length of stay, and left without being seen (LWBS). These indicators are regarded as systemic shortcomings, reflecting a failure to provide equitable and accessible acute care. The objective was to evaluate the effectiveness of interventions aimed at improving ED care delivery indicators. ⋯ Operational strategies such as POC testing and triage liaison physicians could mitigate the impact of ED crowding and appear to be effective. The current evidence supports these strategies when tailored to the appropriate practice environment.
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Review Meta Analysis
Using natural language processing in emergency medicine health service research: A systematic review and meta-analysis.
Natural language processing (NLP) represents one of the adjunct technologies within artificial intelligence and machine learning, creating structure out of unstructured data. This study aims to assess the performance of employing NLP to identify and categorize unstructured data within the emergency medicine (EM) setting. ⋯ Our analysis revealed a generally favorable performance accuracy in using NLP within EM research, particularly in the realm of radiologic interpretation. Consequently, we advocate for the adoption of NLP-based research to augment EM health care management.
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Review Meta Analysis
Using natural language processing in emergency medicine health service research: A systematic review and meta-analysis.
Natural language processing (NLP) represents one of the adjunct technologies within artificial intelligence and machine learning, creating structure out of unstructured data. This study aims to assess the performance of employing NLP to identify and categorize unstructured data within the emergency medicine (EM) setting. ⋯ Our analysis revealed a generally favorable performance accuracy in using NLP within EM research, particularly in the realm of radiologic interpretation. Consequently, we advocate for the adoption of NLP-based research to augment EM health care management.
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The emergency department (ED) is a demanding and time-pressured environment where doctors must navigate numerous team interactions. Conflicts between health care professionals frequently arise in these settings. We aim to synthesize the individual-, team-, and systemic-level factors that contribute to conflict between clinicians within the ED and explore strategies and opportunities for future research. ⋯ In emergency medicine, conflict is common and occurs at multiple levels, reflecting the complex interface of tasks and relationships within ED.