Measuring racial segregation in health system networks using the dissimilarity index

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).

Keywords: Alzheimer's disease and related dementias; End-of-life care; Social networks.

Figure 1:

Example physician patient-sharing networks in a given region.

Figure 2:

Physician Patient-Sharing Network Construction.

Figure 3:

Plot of the dissimilarity index against the percentage of the population of end-of-life patients who are black. Note: The size of the circle is the size of the white patient population.

Figure 4:

Ventiles of physician contribution to the dissimilarity index by HRR.

Figure 5:

Plot of percentage of physician’s patients who are black for the physicians in the highest ventile of contributions to the dissimilarity index within HRR.