Yang et al., "Comparing measures of centrality in bipartite patient-prescriber networks: A study of drug seeking for opioid analgesics" (2022)

Kai-Cheng Yang, Brian Aronson, Meltem Odabas, Yong-Yeol Ahn, and Brea L. Perry, PLOS ONE 17(8), e0273569 (2022)
Link | SocArXiv | Data and code

@article{yang2022comparing,
    title = {Comparing measures of centrality in bipartite patient-prescriber networks: A study of drug seeking for opioid analgesics},
    author = {Kai-Cheng Yang and Brian Aronson and Meltem Odabas and Yong-Yeol Ahn and Brea L. Perry},
    journal = {PLOS ONE},
    volume = {17},
    number = {8},
    pages = {e0273569},
    doi = {10.1371/journal.pone.0273569},
    year = {2022},
}

Compares centrality measures on bipartite patient–prescriber networks built from insurance claims. Two bipartiteness-aware variants predict subsequent opioid overdose better than traditional centrality estimates, and incorporating prescription potency further improves their performance.

Bipartite network, Centrality, Opioid overdose prediction