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Measuring racial segregation in health system networks using the dissimilarity index

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  • Austin, Andrea M.
  • Carmichael, Donald Q.
  • Bynum, Julie P.W.
  • Skinner, Jonathan S.

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).

Suggested Citation

  • Austin, Andrea M. & Carmichael, Donald Q. & Bynum, Julie P.W. & Skinner, Jonathan S., 2019. "Measuring racial segregation in health system networks using the dissimilarity index," Social Science & Medicine, Elsevier, vol. 240(C).
  • Handle: RePEc:eee:socmed:v:240:y:2019:i:c:s0277953619305647
    DOI: 10.1016/j.socscimed.2019.112570
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    References listed on IDEAS

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    1. Fattore, Giovanni & Frosini, Francesca & Salvatore, Domenico & Tozzi, Valeria, 2009. "Social network analysis in primary care: The impact of interactions on prescribing behaviour," Health Policy, Elsevier, vol. 92(2-3), pages 141-148, October.
    2. Rebecca Allen & Simon Burgess & Russell Davidson & Frank Windmeijer, 2015. "More reliable inference for the dissimilarity index of segregation," Econometrics Journal, Royal Economic Society, vol. 18(1), pages 40-66, February.
    3. Ai, Chunrong & Norton, Edward C., 2003. "Interaction terms in logit and probit models," Economics Letters, Elsevier, vol. 80(1), pages 123-129, July.
    4. David Cutler & Jonathan Skinner & Ariel Dora Stern & David Wennberg, 2013. "Physician Beliefs and Patient Preferences: A New Look at Regional Variation in Health Care Spending," NBER Working Papers 19320, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Popescu, Ioana & Gibson, Ben & Matthews, Luke & Zhang, Shiyuan & Escarce, José J. & Schuler, Megan & Damberg, Cheryl L., 2024. "The segregation of physician networks providing care to black and white patients with heart disease: Concepts, measures, and empirical evaluation," Social Science & Medicine, Elsevier, vol. 343(C).

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