Articles: hospital-emergency-service.
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Triage refers to classifying and prioritizing patients based on the severity of their injuries or illnesses in the health care setting. The increasing number of elderly patients seeking care in emergency departments (EDs) highlights the need for special attention to the unique needs of this patient population. ⋯ Significant differences in patients' methods of presentation to the ED were observed based on the MTS, qSOFA, NEWS, and ESI scores.
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Observational Study
Neutrophil-to-lymphocyte ratio as a predictor for outcomes in patients with short-term emergency department revisits.
Analysis of short-term emergency department (ED) revisits is a common emergency care quality assurance practice. Previous studies have explored various risk factors of ED revisits; however, laboratory data were usually omitted. This study aimed to evaluate the prognostic significance of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte (PLR), and systemic immune-inflammation index (SII) in predicting outcomes of patients revisiting the ED. ⋯ The intensity of the inflammatory response expressed by NLR was an independent predictor for poor outcomes of ED revisits and should be considered when ED revisits occur. Future prediction models for ED revisit outcomes can include revisit-NLR as a potential predictor to reflect the progressive conditions in ED patients.
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Health care systems are increasingly screening for unmet social needs. The association between patient-reported social needs and health care utilization is not well understood. ⋯ Patient-reported social needs were common and associated with health care utilization patterns. Future research should identify interventions to address unmet social needs to improve health and avoid potentially preventable escalating medical intervention.
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Emergency department (ED) overcrowding presents a global challenge that inhibits prompt care for critically ill patients. Traditional 5-level triage system that heavily rely on the judgment of the triage staff could fail to detect subtle symptoms in critical patients, thus leading to delayed treatment. Unlike previous rivalry-focused approaches, our study aimed to establish a collaborative machine learning (ML) model that renders risk scores for severe illness, which may assist the triage staff to provide a better patient stratification for timely critical cares. ⋯ The traditional 5-level triage system often falls short, leading to under-triage of critical patients. Our models include a score-based differentiation within a triage level to offer advanced risk stratification, thereby promoting patient safety.
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Methamphetamine-associated cardiomyopathy (MACM) is a known complication of methamphetamine use; however, risk factors and outcomes of patients with MACM are not well understood. ⋯ Patients who developed MACM had traditional risk factors for heart failure and experienced significantly more ED visits, more hospitalizations, and longer hospital stays than matched controls.