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. 2018 Jul 17;8(4):598-625.
doi: 10.1093/tbm/ibx015.

A scoping review of patient-sharing network studies using administrative data

Eva H DuGoff  1 , Sara Fernandes-Taylor  2 , Gary E Weissman  3   4 , Joseph H Huntley  5 , Craig Evan Pollack  5   6
Affiliations

A scoping review of patient-sharing network studies using administrative data

Eva H DuGoff et al. Transl Behav Med. .

Abstract

There is a robust literature examining social networks and health, which draws on the network traditions in sociology and statistics. However, the application of social network approaches to understand the organization of health care is less well understood. The objective of this work was to examine approaches to conceptualizing, measuring, and analyzing provider patient-sharing networks. These networks are constructed using administrative data in which pairs of physicians are considered connected if they both deliver care to the same patient. A scoping review of English language peer-reviewed articles in PubMed and Embase was conducted from inception to June 2017. Two reviewers evaluated article eligibility based upon inclusion criteria and abstracted relevant data into a database. The literature search identified 10,855 titles, of which 63 full-text articles were examined. Nine additional papers identified by reviewing article references and authors were examined. Of the 49 papers that met criteria for study inclusion, 39 used a cross-sectional study design, 6 used a cohort design, and 4 were longitudinal. We found that studies most commonly theorized that networks reflected aspects of collaboration or coordination. Less commonly, studies drew on the strength of weak ties or diffusion of innovation frameworks. A total of 180 social network measures were used to describe the networks of individual providers, provider pairs and triads, the network as a whole, and patients. The literature on patient-sharing relationships between providers is marked by a diversity of measures and approaches. We highlight key considerations in network identification including the definition of network ties, setting geographic boundaries, and identifying clusters of providers, and discuss gaps for future study.

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Figures

Fig 1
Fig 1
PRISMA flowchart of study selection process.
Fig 2
Fig 2
Example of bipartite patient sharing network and one-mode network. (A) Bipartite patient sharing network. Squares represent patients. Circles represent physicians. (B) One-mode patient sharing network. Circles represent physicians.
Fig A1
Fig A1
Illustration of configurations for exponential random graph models. (A) Two-star. (B) Triangle
See this image and copyright information in PMC

Comment in

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