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A Spatial Analysis of Mental Healthcare in Texas

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  • Felipa De Mello-Sampayo

Abstract

This paper discusses competing-destinations formulation of the gravity model for the flows of patients from their residential areas to health supplier regions. This approach explicitly acknowledges the interdependence of the patient between a set of alternative health supplier regions. This competing-destinations-based approach may be implemented as a probabilistic demand function or conditional logit model, with a Poisson outcome. A Texas-based case study of residential areas and State Mental Hospitals (SMHs) is presented. The results of the estimation do not lend support to the presence of scale effects in SMHs due to the size of population. This result, combined with the negative effect of average length of stay and with the positive effect of the provision of forensic services on patient flows, highlights the problem of caseload growth in SMHs.

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  • Felipa De Mello-Sampayo, 2016. "A Spatial Analysis of Mental Healthcare in Texas," Spatial Economic Analysis, Taylor & Francis Journals, vol. 11(2), pages 152-175, June.
    • Handle: RePEc:taf:specan:v:11:y:2016:i:2:p:152-175
    DOI: 10.1080/17421772.2016.1102959
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    Cited by:

    1. Oshan, Taylor M., 2020. "The spatial structure debate in spatial interaction modeling: 50 years on," OSF Preprints 42vxn, Center for Open Science.
    2. Felipa de Mello-Sampayo, 2017. "Competing-destinations gravity model applied to trade in intermediate goods," Applied Economics Letters, Taylor & Francis Journals, vol. 24(19), pages 1378-1384, November.
    3. Lu, Jialiang & Zheng, Xu & Nervino, Esterina & Li, Yanzhi & Xu, Zhihua & Xu, Yabo, 2024. "Retail store location screening: A machine learning-based approach," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).

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