Articles: emergency-department.
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A majority of patients who experience acute coronary syndrome (ACS) initially receive care in the emergency department (ED). Guidelines for care of patients experiencing ACS, specifically ST-segment elevation myocardial infarction (STEMI) are well defined. We examine the utilization of hospital resources between patients with NSTEMI as compared to STEMI and unstable angina (UA). We then make the case that as NSTEMI patients are the majority of ACS cases, there is a great opportunity to risk stratify these patients in the emergency department. ⋯ The sample included 284,945 adult ED patients, of whom 1195 experienced ACS. Among the latter, 978 (70%) were diagnosed with NSTEMI, 225 (16%) with STEMI, and 194 with UA (14%). We observed 79.1% of STEMI patients receiving ICU care. 14.4% among NSTEMI patients, and 9.3% among UA patients. NSTEMI patients' mean hospital LOS was 3.7 days. This was shorter than that of non-ACS patients 4.75 days and UA patients 2.99. In-hospital mortality for NSTEMI was 1.6%, compared to, 4.4% for those with STEMI patients and 0% for UA. There are recommendations for risk stratification among NSTEMI patients to evaluate risk for major adverse cardiac events (MACE) that can be used in the ED to guide admission decisions and use of ICU care, thus optimizing care for a majority of ACS patients.
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I propose a methodology to compare individual emergency physician (EP) work patterns. This is intended to generate discussion within the specialty. A work pattern graph shows individual EP productivity and, assuming the EPs case selection is similar, can be used to compare group activity. Using a simple mathematical model, an averaged calculation can be made of the number of patients needed to be seen by each treating clinician during a standard shift.
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A person's place of residence is a strong risk factor for important diagnosed chronic diseases such as diabetes. It is unclear whether neighborhood-level risk factors also predict the probability of undiagnosed disease. The objective of this study was to identify neighborhood-level variables associated with severe hyperglycemia among emergency department (ED) patients without a history of diabetes. ⋯ Many geospatial exposures were associated with uncontrolled hyperglycemia, even after controlling for individual-level risk factors. The most strongly associated neighborhood-level variables included lower markers of educational attainment, higher percentage of households where limited English is spoken, lower rates of white-collar employment, and higher rates of Medicaid insurance. Including these geospatial factors in risk assessment models may help identify important subgroups of patients with undiagnosed disease.