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Measuring racial segregation in health system networks using the dissimilarity index.

Authors :
Austin, Andrea M.
Carmichael, Donald Q.
Bynum, Julie P.W.
Skinner, Jonathan S.
Source :
Social Science & Medicine. Nov2019, Vol. 240, pN.PAG-N.PAG. 1p.
Publication Year :
2019

Abstract

Racial disparities in the end-of-life treatment of patients are a well observed fact of the U.S. healthcare system. Less is known about how the physicians treating patients at the end-of-life influence the care received. Social networks have been widely used to study interactions with the healthcare system using physician patient-sharing networks. In this paper, we propose an extension of the dissimilarity index (DI), classically used to study geographic racial segregation, to study differences in patient care patterns in the healthcare system. Using the proposed measure, we quantify the unevenness of referrals (sharing) by physicians in a given region by their patients' race and how this relates to the treatments they receive at the end-of-life in a cohort of Medicare fee-for-service patients with Alzheimer's disease and related dementias. We apply the measure nationwide to physician patient-sharing networks, and in a sub-study comparing four regions with similar racial distribution, Washington, DC, Greenville, NC, Columbus, GA, and Meridian, MS. We show that among regions with similar racial distribution, a large dissimilarity index in a region (Washington, DC DI = 0.86 vs. Meridian, MS DI = 0.55), which corresponds to more distinct referral networks for black and white patients by the same physician, is correlated with black patients with Alzheimer's disease and related dementias receiving more aggressive care at the end-of-life (including ICU and ventilator use), and less aggressive quality care (early hospice care). • Novel application of the dissimilarity index to social network analysis. • Considered a cohort of patients with Alzheimer's disease and related dementias. • Analyzed racial disparities in end-of-life treatment intensity. • Large dissimilarity index is associated with more intensive end-of-life treatments. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02779536
Volume :
240
Database :
Academic Search Index
Journal :
Social Science & Medicine
Publication Type :
Academic Journal
Accession number :
139218538
Full Text :
https://doi.org/10.1016/j.socscimed.2019.112570