• Login
    View Item 
    •   UMB Digital Archive
    • School, Graduate
    • Theses and Dissertations All Schools
    • View Item
    •   UMB Digital Archive
    • School, Graduate
    • Theses and Dissertations All Schools
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of UMB Digital ArchiveCommunitiesPublication DateAuthorsTitlesSubjectsThis CollectionPublication DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    Display statistics

    Quantifying Neighborhood-Level Social Determinants of Potentially Preventable Emergency Department Visits in Maryland

    • CSV
    • RefMan
    • EndNote
    • BibTex
    • RefWorks
    Thumbnail
    Name:
    Rowe_umaryland_0373D_10492.pdf
    Size:
    2.998Mb
    Format:
    PDF
    Download
    Author
    Rowe, Gina C.
    Advisor
    Johantgen, Mary E.
    Date
    2013
    Type
    dissertation
    
    Metadata
    Show full item record
    Abstract
    Background: Potentially preventable hospital admissions (PPAs) and emergency department (ED) visits (PPVs) are those that might have been prevented if patients had received better primary care. A significant number of ED visits in the United States and about a third of those in Maryland are "ambulatory care sensitive," or potentially preventable. Geographic variation in PPV rates reflects community-level differences in primary care access, social determinants of health-seeking behavior, and health disparities. Higher rates are noted in poor communities and vulnerable populations. Purpose: To compare and explain the geographic variance in Maryland PPV rates for total and uninsured populations and test the predictive value of regression models developed using generalized linear regression and geographic information systems. Analysis of geographic variance in PPV rates across the Baltimore metropolitan statistical area (MSA) used neighborhood-level social determinants to determine whether social capital can mediate the negative impact of living in a disadvantaged neighborhood on PPV rates. Methods: Two cross-sectional, ecologic regression analyses of secondary data aggregated to the zip code tabulation level were conducted. Generalized linear and geographic regression models were built using SPSS and ArcGIS statistical software, and results were compared to determine which model(s) best explained geographic variance in PPV rates. Social capital measures were obtained from the Baltimore Ecosystem Study. Results: In Maryland, geographic hot spots of increased PPV rates were highly correlated for uninsured and total populations, but uninsured PPV rates were more clustered in urban areas. Poisson and geographically weighted regression (GWR) models explained the most PPV rate variance. Significant predictors were per capita income, female-headed households, and level of education. In the Baltimore MSA, Poisson and GWR models predicted 85-86% of PPV rate variance; relative poverty and female-headed households were significant predictors but percent uninsured and per capita primary care physicians were not. Social capital was a significant partial mediator of all measures of neighborhood disadvantage reviewed. Conclusion: Communities with high social capital may offer health-protective benefits to residents, even mediating the negative impact of living in a disadvantaged neighborhood. Reducing PPVs requires consideration of population-level health-seeking behaviors and promotion of neighborhood-level social capital, particularly for single mothers.
    Description
    University of Maryland, Baltimore. Nursing. Ph.D. 2013
    Keyword
    ambulatory care sensitive conditions
    geographic variance
    neighborhood disadvantage
    social capital
    Neighborhoods--health aspects
    Emergency Medical Services
    Health Services Accessibility
    Maryland
    Primary Health Care--utilization
    Social Determinants of Health
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/3652
    Collections
    Theses and Dissertations School of Nursing
    Theses and Dissertations All Schools

    entitlement

     
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Quick Guide | Policies | Contact Us | UMB Health Sciences & Human Services Library
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.