Abstract
This study explores the forces that drive the formation of physician patient sharing networks. In particular, I examine the degree to which hospital affiliation drives physicians' sharing of Medicare patients. Using a revealed preference framework where observed network links are taken to be pairwise stable, I estimate the physicians' pair‐specific values using a tetrad maximum score estimator that is robust to the presence of unobserved physician specific characteristics. I also control for a number of potentially confounding patient sharing channels, such as (a) common physician group or hospital system affiliation, (b) physician homophily, (c) knowledge complementarity, (d) patient side considerations related to both geographic proximity and insurance network participation, and (e) spillover from other collaborations. Focusing on the Chicago hospital referral region, I find that shared hospital affiliation accounts for 36.5% of the average pair‐specific utility from a link. Implications for reducing care fragmentation are discussed.
Highlights
Recent work has helped uncover important relationships between the underlying structure of physician patient sharing networks and overall health care outcomes (Barnett, Song, & Landon, 2012a; Landon et al, 2018)
One hurdle in accomplishing this aim has been that establishing a credible case for causality in the presence of unobservable physician specific characteristics that may play a role in physician patient sharing is problematic in social network settings where the researcher commonly works with cross sectional data on a sparse network that exhibits considerable degree heterogeneity
The equilibrium notion of pairwise stability provides me with inequalities that are used to estimate the parameters of physicians' link specific utility, which allows me to account for physicians' degree heterogeneity that may stem from physician‐specific unobservables
Summary
Recent work has helped uncover important relationships between the underlying structure of physician patient sharing networks and overall health care outcomes (Barnett, Song, & Landon, 2012a; Landon et al, 2018). Fragmented service delivery occurs when a patient is seen by a large number of physicians, introducing risk for lapses in coordination of care, with growing evidence that network structures with large numbers of specialist providers (i.e., higher levels of fragmented care) are associated with higher health care utilization and higher costs (Agha, Marzilli Ericson, Geissler, & Rebitzer, 2018; Agha, Frandsen, & Rebitzer, 2019). One hurdle in accomplishing this aim has been that establishing a credible case for causality in the presence of unobservable physician specific characteristics that may play a role in physician patient sharing (e.g., unobserved reputation or quality measures) is problematic in social network settings where the researcher commonly works with cross sectional data on a sparse network that exhibits considerable degree heterogeneity (see, e.g., Chandrasekhar, 2016; Graham, 2017).. The equilibrium notion of pairwise stability provides me with inequalities that are used to estimate the parameters of physicians' link specific utility (using a tetrad maximum score estimator), which allows me to account for physicians' degree heterogeneity that may stem from physician‐specific unobservables
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