When Clinicians Group Together: A Systematic Scoping Review of Clustering in Patient-Sharing Networks

Abstract

Background . Improvements in patient safety and quality of care can be achieved by improvements in clinicians’ teamwork, coordination and communication. Growing research examines the structure and dynamics of clinician networks using social network analysis. Such networks can have clusters of healthcare professionals within them, but systematized knowledge on these clusters is lacking. Our goal was to review the evidence on determinants and characteristics of healthcare professional clustering in patient-sharing networks and their associations with patient outcomes. Methods. We searched for English-language peer-reviewed studies published up until January 4, 2021 using PubMed and EMBASE and an existing scoping review on patient-sharing by DuGoff et al (2018). We performed a systematic scoping review in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We performed title and abstract screening and full-text screening to identify studies that used social network analysis to examine relationships between patient-sharing network clusters and health outcomes. From the twelve eligible studies, we extracted study information such as study design and setting, population, patient-sharing definition, network measures, clustering definition, health outcomes, and reported associations. Results. The studies varied considerably in definitions and measures of patient-sharing relations, definitions and structural measures of network clusters, settings, study population, and health outcomes. The general patterns indicate that busier physician networks (i.e., networks with more connections among physicians) are associated with worse health outcomes and better-connected physician networks are associated with better health outcomes. Conclusion. The majority of existing studies are exploratory. Rigorous theoretical grounding, interventional studies, and mixed-methods studies would help to strengthen patient-sharing research and advance our understanding of how patient-sharing clustering affects patient outcomes.