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{
    "pk": 16794,
    "title": "Assessing the Relationship Between Race, Language, and Surgical Admissions in the Emergency Department",
    "subtitle": null,
    "abstract": "Introduction: English proficiency and race are both independently known to affect surgical access and quality, but relatively little is known about the impact of race and limited English proficiency (LEP) on admission for emergency surgery from the emergency department (ED). Our objective was to examine the influence of race and English proficiency on admission for emergency surgery from the ED.\nMethods: We conducted a retrospective observational cohort study from January 1–December 31, 2019 at a large, quaternary-care urban, academic medical center with a 66-bed ED Level I trauma and burn center. We included ED patients of all self-reported races reporting a preferred language other than English and requiring an interpreter or declaring English as their preferred language (control group). A multivariable logistic regression was fit to assess the association of LEP status, race, age, gender, method of arrival to the ED, insurance status, and the interaction between LEP status and race with admission for surgery from the ED.\nResults: A total of 85,899 patients (48.1% female) were included in this analysis, of whom 3,179 (3.7%) were admitted for emergent surgery. Regardless of LEP status, patients identifying as Black (odds ratio [OR] 0.456, 95% CI 0.388-0.533; P<0.005), Asian [OR 0.759, 95% CI 0.612-0.929]; P=0.009), or female [OR 0.926, 95% CI 0.862-0.996]; P=0.04) had significantly lower odds for admission for surgery from the ED compared to White patients. Compared to individuals on Medicare, those with private insurance [OR 1.25, 95% CI 1.13-1.39; P <0.005) were significantly more likely to be admitted for emergent surgery, whereas those without insurance [OR 0.581, 95% CI 0.323-0.958; P=0.05) were significantly less likely to be admitted for emergent surgery. There was no significant difference in odds of admission for surgery between LEP vs non-LEP patients.\nConclusion: Individuals without health insurance and those identifying as female, Black, or Asian had significantly lower odds of admission for surgery from the ED compared to those with health insurance, males, and those self-identifying as White, respectively. Future studies should assess the reasons underpinning this finding to elucidate impact on patient outcomes.",
    "language": "en",
    "license": {
        "name": "Creative Commons Attribution 4.0",
        "short_name": "CC BY 4.0",
        "text": "Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.\r\n\r\nNo additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.",
        "url": "https://creativecommons.org/licenses/by/4.0"
    },
    "keywords": [
        {
            "word": "Race"
        },
        {
            "word": "disparities"
        },
        {
            "word": "emergency department"
        },
        {
            "word": "Surgery"
        },
        {
            "word": "Emergency Surgery"
        }
    ],
    "section": "Health Equity",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/3wr273s6",
    "frozenauthors": [
        {
            "first_name": "Grant",
            "middle_name": "",
            "last_name": "Rigney",
            "name_suffix": "",
            "institution": "Harvard Medical School, Boston, Massachusetts; Massachusetts General Hospital, Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Boston, Massachusetts",
            "department": "None"
        },
        {
            "first_name": "Soham",
            "middle_name": "",
            "last_name": "Ghoshal",
            "name_suffix": "",
            "institution": "Harvard Medical School, Boston, Massachusetts; Massachusetts General Hospital, Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Boston, Massachusetts",
            "department": "None"
        },
        {
            "first_name": "Sarah",
            "middle_name": "",
            "last_name": "Mercaldo",
            "name_suffix": "",
            "institution": "Massachusetts General Hospital, Department of Radiology, Boston, Massachusetts",
            "department": "None"
        },
        {
            "first_name": "Debby",
            "middle_name": "",
            "last_name": "Cheng",
            "name_suffix": "",
            "institution": "Harvard Medical School, Boston, Massachusetts; Massachusetts General Hospital, Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Boston, Massachusetts",
            "department": "None"
        },
        {
            "first_name": "Jonathan",
            "middle_name": "J",
            "last_name": "Parks",
            "name_suffix": "",
            "institution": "Harvard Medical School, Boston, Massachusetts; Massachusetts General Hospital, Department of Surgery, Boston, Massachusetts",
            "department": "None"
        },
        {
            "first_name": "George",
            "middle_name": "C",
            "last_name": "Velmahos",
            "name_suffix": "",
            "institution": "Harvard Medical School, Boston, Massachusetts; Massachusetts General Hospital, Department of Surgery, Boston, Massachusetts",
            "department": "None"
        },
        {
            "first_name": "Michael",
            "middle_name": "",
            "last_name": "Lev",
            "name_suffix": "",
            "institution": "Harvard Medical School, Boston, Massachusetts; Massachusetts General Hospital, Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Boston, Massachusetts; Massachusetts General Hospital, Department of Radiology, Boston, Massachusetts",
            "department": "None"
        },
        {
            "first_name": "Ali",
            "middle_name": "S",
            "last_name": "Raja",
            "name_suffix": "",
            "institution": "Harvard Medical School, Boston, Massachusetts; Massachusetts General Hospital, Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Boston, Massachusetts; Massachusetts General Hospital, Department of Emergency Medicine, Boston, Massachusetts",
            "department": "None"
        },
        {
            "first_name": "Efren",
            "middle_name": "J",
            "last_name": "Flores",
            "name_suffix": "",
            "institution": "Harvard Medical School, Boston, Massachusetts; Massachusetts General Hospital, Department of Radiology, Boston, Massachusetts",
            "department": "None"
        },
        {
            "first_name": "Marc",
            "middle_name": "D",
            "last_name": "Succi",
            "name_suffix": "",
            "institution": "Harvard Medical School, Boston, Massachusetts; Massachusetts General Hospital, Medically Engineered Solutions in Healthcare Incubator, Innovation in Operations Research Center (MESH IO), Boston, Massachusetts; Massachusetts General Hospital, Department of Radiology, Boston, Massachusetts",
            "department": "None"
        }
    ],
    "date_submitted": "2022-05-01T19:04:26Z",
    "date_accepted": "2022-05-01T19:04:26Z",
    "date_published": "2023-02-01T19:29:30Z",
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            "type": "pdf",
            "path": "https://journalpub.escholarship.org/westjem/article/16794/galley/8505/download/"
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}