TexasScholarWorks
    • Login
    • Submit
    View Item 
    •   Repository Home
    • UT Electronic Theses and Dissertations
    • UT Electronic Theses and Dissertations
    • View Item
    • Repository Home
    • UT Electronic Theses and Dissertations
    • UT Electronic Theses and Dissertations
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Estimation of direct and indirect costs of treating schizophrenia for community-dwelling US residents

    Thumbnail
    View/Open
    DESAI-THESIS.pdf (1.107Mb)
    Date
    2011-12
    Author
    Desai, Pooja Rajiv
    Share
     Facebook
     Twitter
     LinkedIn
    Metadata
    Show full item record
    Abstract
    Schizophrenia is a chronic and debilitating disease that affects approximately one percent of the US population and exerts a disproportionately high financial burden on the society. The objective of this study was to estimate the direct and indirect costs of schizophrenia among community-dwelling US residents and identify patient characteristics associated with high schizophrenia-related direct costs. Patients with a diagnosis of schizophrenia (ICD-9 code 295) or other non-organic psychoses (ICD-9 code 298) between January 1, 2005 and December 31, 2008 were identified from the Medical Expenditure Panel Survey (MEPS). To estimate direct costs, the following cost categories were identified: inpatient hospitalizations, outpatient visits, emergency department visits, office-based physician visits, home healthcare visits, and prescription medications. The following cost categories were identified to estimate indirect costs: caregivers’ costs and cost of lost productivity due to missed work days, reduced employment, and suicide. Logistic regression was used to compare patients belonging to the high-cost group and to the low-cost group. All analyses were carried out using SAS version 9.2 (SAS Institute Inc., Cary, North Carolina). The weighted average number of patients with schizophrenia identified for each year was 757,893. The annual direct and indirect costs were estimated at $3.96 billion and $15.35 billion, respectively. The mean annual direct medical schizophrenia-related cost per patient was $5,586. For each one-year increase in age, patients were 5.7% less likely to be in the high-cost group. Patients with a spouse were 77.7% less likely than patients without a spouse to be in the high-cost group. Healthcare providers and policymakers can use these cost estimates to better understand the economic burden of schizophrenia and identify services and subgroups of patients associated with the highest costs. This would help in the provision of healthcare services to patients with schizophrenia and in the optimization of patient outcomes.
    Department
    Pharmacy
    Description
    text
    Subject
    Schizophrenia
    Costs
    Medical Expenditure Panel Survey (MEPS)
    URI
    http://hdl.handle.net/2152/ETD-UT-2011-12-4498
    Collections
    • UT Electronic Theses and Dissertations

    University of Texas at Austin Libraries
    • facebook
    • twitter
    • instagram
    • youtube
    • CONTACT US
    • MAPS & DIRECTIONS
    • JOB OPPORTUNITIES
    • UT Austin Home
    • Emergency Information
    • Site Policies
    • Web Accessibility Policy
    • Web Privacy Policy
    • Adobe Reader
    Subscribe to our NewsletterGive to the Libraries

    © The University of Texas at Austin

     

     

    Browse

    Entire RepositoryCommunities & CollectionsDate IssuedAuthorsTitlesSubjectsDepartmentsThis CollectionDate IssuedAuthorsTitlesSubjectsDepartments

    My Account

    Login

    Statistics

    View Usage Statistics

    Information

    About Contact Policies Getting Started Glossary Help FAQs

    University of Texas at Austin Libraries
    • facebook
    • twitter
    • instagram
    • youtube
    • CONTACT US
    • MAPS & DIRECTIONS
    • JOB OPPORTUNITIES
    • UT Austin Home
    • Emergency Information
    • Site Policies
    • Web Accessibility Policy
    • Web Privacy Policy
    • Adobe Reader
    Subscribe to our NewsletterGive to the Libraries

    © The University of Texas at Austin