Problem opioid use and opioid-related drug overdoses remain a major public health concern despite attempts to reduce and monitor opioid prescriptions and increase access to office-based opioid treatment. Current provider-focused interventions are implemented at the federal, state, regional, and local levels but have not slowed the epidemic. Certain targeted interventions aimed at opioid prescribers rely on populations defined along geographic, political, or administrative boundaries; however, those boundaries may not align well with actual provider-patient communities or with the geographic distribution of high-risk opioid use. Instead of relying exclusively on commonly used geographic and administrative boundaries, we suggest augmenting existing strategies with a social network-based approach to identify communities (or clusters) of providers that prescribe to the same set of patients as another mechanism for targeting certain interventions. To test this approach, we analyze 1 year of prescription data from a commercially insured population in the state of Indiana. The composition of inferred clusters is compared to Indiana's Public Health Preparedness Districts (PHPDs). We find that in some cases the correspondence between provider networks and PHPDs is very high, while in other cases the overlap is low. This has implications for whether an intervention is reaching its intended provider targets efficiently and effectively. Assessing the best intervention targeting strategy for a particular outcome could facilitate more effective interventions to tackle the ongoing opioid use epidemic.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10474636 | PMC |
http://dx.doi.org/10.1186/s12954-023-00840-8 | DOI Listing |
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