The segregation of physician networks providing care to black and white patients with heart disease: Concepts, measures, and empirical evaluation.

Black-White disparities in cardiac care may be related to physician referral network segregation. We developed and tested new geographic physician network segregation measures. We used Medicare claims to identify Black and White Medicare heart disease patients and map physician networks for 169 hospital referral regions (HRRs) with over 1000 Black patients. We constructed two network segregation indexes ranging from 0 (integration) to 100 (total segregation): Dissimilarity (the unevenness of Black and White patient distribution across physicians [Dn]) and Absolute Clustering (the propensity of Black patients' physicians to have closer ties with each other than with other physicians [ACLn]). We employed conditional logit models to estimate the probability of using the best (lowest mortality) geographically available hospital for Black and White patients undergoing coronary artery bypass grafting (CABG) surgery in 126 markets with sufficient sample size at increasing levels of network segregation and for low vs. high HRR Black patient population. Physician network segregation was lower than residential segregation (Dissimilarity 21.9 vs. 48.7, and Absolute Clustering 4.8 vs. 32.4) and positively correlated with residential segregation (p < .001). Network segregation effects differed by race and HRR Black patient population. For White patients, higher network segregation was associated with a higher probability of using the best available hospitals in HRRs with few black patients but unchanged (ACLn) or lower (Dn) probability of best hospital use in HRRs with many Black patients. For Black patients, higher network segregation was not associated with a substantial change in the probability of best hospital use regardless of the HRR Black patient population size. Measuring physician network segregation is feasible and associated with nuanced effects on Black-White differences in high-quality hospital use for heart disease. Further work is needed to understand underlying mechanisms and potential uses in health equity policy.

Efficacy of the Best Possible Self protocol in diabetes self-management: A mixed-methods approach.

Recent research has demonstrated that positive affect may facilitate illness self-management. This study used a sequential exploratory mixed-methods typology to assess whether a brief writing task designed to boost positive affect (the Best Possible Self protocol) could improve aspects of diabetes self-management, specifically. A qualitative investigation explored people with diabetes' (n = 20) views regarding Best Possible Self feasibility and acceptability, while a subsequent quantitative investigation assigned people with diabetes (n = 50) to a Best Possible Self or non-Best Possible Self condition and assessed affect and self-management behaviours over a 4-week period. Findings indicated that individuals were receptive to the Best Possible Self and that it provided benefits for diabetes self-management.