BACKGROUND: Research on the quality and cost of care traditionally focuses on individual physicians or medical groups. Social network theory suggests that the care a patient receives also depends on the network of physicians with whom a patient's physician is connected. OBJECTIVES: The objectives of the study are: (1) identify physician networks; (2) determine whether the rate of ambulatory care-sensitive hospital admissions (ACSAs) varies across networks--even different networks at the same hospital; and (3) determine the relationship between ACSA rates and network characteristics. RESEARCH DESIGN: We identified networks by applying network detection algorithms to Medicare 2008 claims for 987,000 beneficiaries in 5 states. We estimated a fixed-effects model to determine the relationship between networks and ACSAs and a multivariable model to determine the relationship between network characteristics and ACSAs. RESULTS: We identified 417 networks. Mean size: 129 physicians; range, 26-963. In the fixed-effects model, ACSA rates varied significantly across networks: there was a 46% difference in rates between networks at the 25th and 75th performance percentiles. At 95% of hospitals with admissions from 2 networks, the networks had significantly different ACSA rates; the mean difference was 36% of the mean ACSA rate. Networks with a higher percentage of primary-care physicians and networks in which patients received care from a larger number of physicians had higher ACSA rates. CONCLUSIONS: Physician networks have a relationship with ACSAs that is independent of the physicians in the network. Physician networks could be an important focus for understanding variations in medical care and for intervening to improve care.
China's HIV prevalence is low, mainly concentrated among female sex workers (FSWs), their clients, men who have sex with men, and the stable partners of members of these high-risk groups. We evaluate the contribution to the spread of HIV of China's regime of heterosexual relations, of the structure of heterosexual networks, and of the attributes of key population groups with simulations driven by data from a cross-sectional survey of egocentric sexual networks of the general population of Shanghai and from a concurrent respondent-driven sample of FSWs. We find that the heterosexual network generated by our empirically calibrated simulations has low levels of partner change, strong constraints on partner selection by age and education, and a very small connected core, mainly comprising FSWs and their clients and characterized by a fragile transmission structure. This network has a small HIV epidemic potential but is compatible with the transmission of bacterial sexually transmitted infections (STIs), such as syphilis, which are less susceptible to structural breaks in transmission of infection. Our results suggest that policies that force commercial sex underground could have an adverse effect on the spread of HIV and other STIs.
We explore the network coverage of a sample of female sex workers (FSWs) in China recruited through Respondent Drive Sampling (RDS) as part of an effort to evaluate the claim of RDS of population representation with empirical data. We take advantage of unique information on the social networks of FSWs obtained from two overlapping studies--RDS and a venue-based sampling approach (PLACE)--and use an exponential random graph modeling (ERGM) framework from local networks to construct a likely network from which our observed RDS sample is drawn. We then run recruitment chains over this simulated network to assess the assumption that the RDS chain referral process samples participants in proportion to their degree and the extent to which RDS satisfactorily covers certain parts of the network. We find evidence that, contrary to assumptions, RDS oversamples low degree nodes and geographically central areas of the network. Unlike previous evaluations of RDS which have explored the performance of RDS sampling chains on a non-hidden population, or the performance of simulated chains over previously mapped realistic social networks, our study provides a robust, empirically grounded evaluation of the performance of RDS chains on a real-world hidden population.