Prediction Model of Disparities in Health Coverage Among Psychiatric Inpatients

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dc.contributor.authorOmary, Areen
dc.date.accessioned2020-07-15T14:39:36Z
dc.date.available2020-07-15T14:39:36Z
dc.date.issued2020-03-05
dc.descriptionResearch dataset has produced several studies and accepted and presented at several national conferences in 2018 and 2019 including the Annual Research Meeting of Academy Health sponsored by Patient Centered Research Institute in Washington DC and the Annual Meeting sponsored by the Council of Social Work Education in Orlando, FL. Omary, A. National estimates of prevalence and correlates of major depression among hospital discharged patients. Poster presentation at the Annual Research Meeting Conference. Academy Health. Washington D.C. (June 2-4, 2019). Accepted. https://academyhealth.confex.com/academyhealth/2019arm/meetingapp.cgi/Paper/31133 Omary, A. Multinomial Logistic Regression Model for Predicting Disparities in Health Coverage among Psychiatric Inpatients. Poster presentation at the Annual Research Meeting Conference. Academy Health. Seattle, WA (June 24-26, 2018). Accepted. https://academyhealth.confex.com/academyhealth/2018arm/meetingapp.cgi/Paper/23578 Omary, A. Prediction Model of Disparities in Health Coverage Among Psychiatric Inpatients. Poster presentation at the Annual Program Meeting. Council of Social Work Education. Orlando, FL (November 8-11, 2018). Accepted.en_US
dc.description.abstractThe goal of this study was to examine the demographics sex and marital status of inpatients with schizophrenia and bipolar and compare differences in patients’ chances of possessing adequate health coverage to cover hospital expenses. Data from the National Hospital Discharge Survey was extracted and analyzed. For hospital discharges of patients age 18 and older 702,626 hospital discharges were included in the study representing a weighted population of 77,082,738 hospital discharges. Prediction model was applied to test the ability of the independent variables sex and marital status to predict differences in health coverage in multinomial logistic regression (MLR) test. Results indicate that sex and marital status were significant predictors of health coverage type that the patient owned. Male, unmarried, and with unknown marital status patients were more likely to be either uninsured or publicly insured. Public health policy legislation efforts need to address public-health-insurance provisions that limit the coverage of treatment for psychiatric patients.en_US
dc.identifier.citationOmary, A. (2019). Disparities in health coverage across gender and marital status among discharged psychiatric patients. Psychiatric Quarterly, 90 (2):461-469. doi:10.1007/s11126-019-09637-0en_US
dc.identifier.urihttps://hdl.handle.net/11310/291
dc.language.isoen_USen_US
dc.publisherWTAMU Cornette Libraryen_US
dc.titlePrediction Model of Disparities in Health Coverage Among Psychiatric Inpatientsen_US
dc.typePresentationen_US

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2020 Faculty Research Poster Session and Research Fair