Abstract

<h3>Objective:</h3> To estimate the probability of admission among patients with stroke evaluated in the emergency department. <h3>Background:</h3> Misuse of inpatient resources is a central problem to the healthcare system. Elucidating certain trends behind inpatient admission in patients with a cerebral infarction may reveal opportunities to improve safe and effective stroke triage and throughput. <h3>Design/Methods:</h3> We retrospectively queried the 2019 National Emergency Department Sample Database for patients who had a cerebral infarction. Disposition from the emergency department was classified into one of several categories: routine discharge, discharge against medical advice, transfer to short term hospital, home care, death, and admission to the inpatient setting. The primary endpoint was inpatient admission versus all other dispositions and was assessed using multivariable logistic regression after adjustment for key patient characteristics, hospital teaching and trauma status, geographic regions, insurance status. <h3>Results:</h3> Of the 598,818 patients diagnosed with acute cerebral infarction, 471,464 (78.7%) were admitted to an inpatient acute care facility. Patients with private insurance (OR 0.85, 95%CI 0.78–0.93) or self-pay (OR 0.80, 95%CI 0.70–0.91) had lower odds of being admitted, compared to Medicare patients. Compared to Metropolitan Non-Teaching hospitals, Metropolitan teaching hospitals (OR 1.59, 95%CI 1.27–1.97) had a higher odds of admission, whereas non-metropolitan hospitals (OR 0.35, 95%CI 0.27–0.44) had a lower odds of admission. Additionally, compared to non-trauma hospitals, patients evaluated at level 1 trauma centers (OR 3.17, 95%CI 2.48–4.05) had higher odds of admission. In addition, hyperlipidemia (OR 2.25, 95%CI 2.09–2.42), overweight (OR 2.15, 95%CI 1.90–2.42), and hypertension (OR 1.55, 95%CI 1.47–1.63) were independently associated with a higher odds of admission. <h3>Conclusions:</h3> Optimization of certain high-risk comorbidities may not only reduce stroke incidence, but they may reduce inpatient utilization. Further, differences in admission based on patient-level socioeconomic factors warrant greater exploration to minimize disparities in access to acute care. <b>Disclosure:</b> Mr. Wolfe has nothing to disclose. Karan Patel has nothing to disclose. Mr. Taneja has nothing to disclose. Mr. Oak has nothing to disclose. The institution of Dr. Favilla has received research support from National Institutes of Health. The institution of Dr. Favilla has received research support from American Heart Association. The institution of Dr. Favilla has received research support from OpenWater, Inc.. An immediate family member of Dr. Thon has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Horizon. An immediate family member of Dr. Thon has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Genentech. An immediate family member of Dr. Thon has received personal compensation in the range of $500-$4,999 for serving on a Speakers Bureau for Genentech. Dr. Thon has received personal compensation in the range of $500-$4,999 for serving as a Focus group participant with Alexion. Dr. Siegler has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Ceribell. Dr. Siegler has received personal compensation in the range of $10,000-$49,999 for serving on a Speakers Bureau for AstraZeneca.

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