IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0273569.html
   My bibliography  Save this article

Comparing measures of centrality in bipartite patient-prescriber networks: A study of drug seeking for opioid analgesics

Author

Listed:
  • Kai-Cheng Yang
  • Brian Aronson
  • Meltem Odabas
  • Yong-Yeol Ahn
  • Brea L Perry

Abstract

Visiting multiple prescribers is a common method for obtaining prescription opioids for nonmedical use and has played an important role in fueling the United States opioid epidemic, leading to increased drug use disorder and overdose. Recent studies show that centrality of the bipartite network formed by prescription ties between patients and prescribers of opioids is a promising indicator for drug seeking. However, node prominence in bipartite networks is typically estimated with methods that do not fully account for the two-mode topology of the underlying network. Although several algorithms have been proposed recently to address this challenge, it is unclear how these algorithms perform on real-world networks. Here, we compare their performance in the context of identifying opioid drug seeking behaviors by applying them to massive bipartite networks of patients and providers extracted from insurance claims data. We find that two variants of bipartite centrality are significantly better predictors of subsequent opioid overdose than traditional centrality estimates. Moreover, we show that incorporating non-network attributes such as the potency of the opioid prescriptions into the measures can further improve their performance. These findings can be reproduced on different datasets. Our results demonstrate the potential of bipartiteness-aware indices for identifying patterns of high-risk behavior.

Suggested Citation

  • Kai-Cheng Yang & Brian Aronson & Meltem Odabas & Yong-Yeol Ahn & Brea L Perry, 2022. "Comparing measures of centrality in bipartite patient-prescriber networks: A study of drug seeking for opioid analgesics," PLOS ONE, Public Library of Science, vol. 17(8), pages 1-22, August.
  • Handle: RePEc:plo:pone00:0273569
    DOI: 10.1371/journal.pone.0273569
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0273569
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0273569&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0273569?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Douglas C McDonald & Kenneth E Carlson, 2013. "Estimating the Prevalence of Opioid Diversion by “Doctor Shoppers” in the United States," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-11, July.
    2. Takahashi, Yoshimitsu & Ishizaki, Tatsuro & Nakayama, Takeo & Kawachi, Ichiro, 2016. "Social network analysis of duplicative prescriptions: One-month analysis of medical facilities in Japan," Health Policy, Elsevier, vol. 120(3), pages 334-341.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zykova, Yana V. & Mannberg, Andrea & Myrland, Øystein, 2022. "Effects of ‘doctor shopping’ behaviour on prescription of addictive drugs in Sweden," Social Science & Medicine, Elsevier, vol. 296(C).

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0273569. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.