Evidence map›Paper›PMID 40703227›Full record

ArticleApplied network science2025

The association of prescriber prominence in a shared-patient physician network with their patients receipt of and transitions between risky drug combinations.

A James O'Malley, Ellen Meara, Nancy E Morden, Erika L Moen, Xin Ran

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Article in Applied network science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

A James O'MalleyDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756 USA.
Ellen MearaDepartment of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, MA 02115 USA.
Nancy E MordenThe Dartmouth Institute for Health Policy and Clinical Practice, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756 USA.
Erika L MoenDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756 USA.
Xin RanDepartment of Biomedical Data Science, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756 USA.

Funding

UNDERSTANDING AND IMPROVING EPISODE-BASED HOSPITAL CAREP01AG019783 · NIA · DARTMOUTH COLLEGE · PI AMBER E BARNATO · 2001 to 2026
$52.9M
NIA NIH HHS P01 AG019783
6 · The paper itself

Abstract

We are generally interested in the association between a prescribing physician's position in a physician shared-patient network and their patients' receipt of risky drug combinations. An informal physician network (not restricted to a hospital or a health system) of physicians based in Ohio was constructed based on overlapping care of patients between physicians reflected in face-to-face visits in Fee-for-service Medicare claims for Ohio-residing beneficiaries. Separately, Medicare prescription drug events for beneficiaries receiving opioids, benzodiazepines, or non-benzodiazepine sedative hypnotics (sedative hypnotics) prescribed by these physicians in 2014 were used to map patients' drug status with respect to these three classes. We assigned patient prescription receipt to time-varying drug states and linked each drug state transition to a "responsible" prescribing physician. Outcomes of interest include transitions across drug states, particularly those resulting in combinations of increased risk (e.g., a benzodiazepine or sedative hypnotic with an opioid), and patients' time to discontinuation of overlapping prescriptions of an opioid, benzodiazepine, and a sedative hypnotic while the key predictors of these transitions reflected characteristics of a prescriber's physician network position and physician speciality. We found that among beneficiaries receiving none of the three risky drug groups, patients seeing physicians with higher closeness centrality (shorter average path lengths to other physicians through the network) were less likely to transition to two or three risky drugs; and they were more likely to discontinue overlapping prescriptions of an opioid, benzodiazepine, and sedative hypnotic. Compared to PCPs, psychiatrists appeared more likely to prescribe risky drug combinations, and their patients were less likely to discontinue overlapping three-drug prescriptions. This work demonstrates that characterizing physicians' prescribing behavior in relation to their position in shared-patient networks may reveal strategies for optimizing network-based interventions to improve prescribing quality. Supplementary Information: The online version contains supplementary material available at 10.1007/s41109-025-00721-y.

Indexed as

DeprescribingNetwork centralityPhysician shared-patient networkPolypharmacyRisky prescribingState-spaceTransition matrix

Identifiers

PMID40703227
PMCPMC12279612

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.