ArticlePLOS digital health2026
Reconstructing healthcare networks from patient transfer data: A systematic review.
Article in PLOS digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Healthcare facilities are interconnected via patient transfers, facilitating pathogen spread. We systematically reviewed studies reconstructing patient-sharing networks. Following PRISMA 2020 guidelines and a preregistered protocol (CRD42024559127), we searched PubMed, Scopus and IEEE Xplore up to October 1, 2025. We included articles presenting networks of at least three healthcare facilities or units connected by observed patient transfers, excluding those restricted to specific patient groups. Seventy-nine articles were included from 5,721 screened, describing 50 distinct networks published across multiple disciplines. Overall confidence in study findings, assessed through a modified QuADS tool, was good (mean total score of 21/33), although precision in the description of underlying patient transfer data was often limited. Most networks were reconstructed in Europe and North America. The majority were restricted to hospitals, with nursing homes and other healthcare facilities rarely integrated, and 10 (20%) used temporal network approaches. While most articles reported descriptive statistics and network metrics, they focused mainly on density and degree (and its variants), with other metrics only rarely calculated. Only 27 (35%) articles developed mathematical models of pathogen transmission, including 12 that simulated public health interventions. Overall, this review highlights the value of patient-sharing networks to characterize healthcare connectivity and understand pathogen spread. Clearly articulating the methodological assumptions underlying network reconstruction and tailoring them to specific research questions is key to fully leveraging the reconstructed networks for public health purposes. In particular, including a broader range of facility types and more temporal modelling can help develop more realistic models of pathogen spread over these networks. This review was funded by the French National Research Agency (ANR 22-PAMR-0003).
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Registered trials
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