Empirical and Normative Implications of Social Networks for Disparities: The Case of Renal Transplantation
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CitationLadin, Keren. 2013. Empirical and Normative Implications of Social Networks for Disparities: The Case of Renal Transplantation. Doctoral dissertation, Harvard University.
AbstractThis dissertation examines the extent to which individual-level and social network-level factors explain disparities in living donor kidney transplantation (LDKT) and considers the moral implications. Paper One examines whether patient characteristics explain racial disparities in the rate of donor presentation and LDKT in a sample of 752 potential kidney recipients and 654 potential kidney donors. Propensity score matching and subclassification were used to balance the patient characteristics. Survival models revealed that only 24% of blacks compared to 39% of whites would have at least one potential donor evaluated within the first year, even after accounting for differences in the distribution of patient characteristics. Thus, lower rates of donor presentation among black recipients cannot be explained by differences in individual-level characteristics. Paper Two examines whether differences in social networks contribute to disparities in LDKT. Using interview and medical record data from a representative sample of 389 dialysis patients in Greater Boston and a subsample of 302 alters, we found that social network characteristics, especially network size, were strongly predictive of pursuing LDKT. Significant racial disparities in health and medical distrust among social networks of black patients present compelling evidence for network effects. Fewer network members of black patients may be eligible for donation owing to compositional health differences, and those eligible may be less willing to donate due to greater distrust or poor socioeconomic position. Paper Three argues that society ought to be concerned with previously neglected disparities in LDKT, specifically the fraction stemming from disparities in social networks because networks provide one pathway by which inequalities can be perpetuated throughout society and over time. Insofar as social networks are influenced by an unjust distribution of social forces, and social networks influence life chances by restricting (or enhancing) one’s ability to obtain a LDKT, then life chances of dialysis patients are unjustly determined by social networks. Potential policies aimed at providing compensatory damages to patients whose networks have been adversely affected by the unjust influence of social determinants are examined.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:10984975
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