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Can peer effects explain prescribing appropriateness? a social network analysis.

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Physician network connections impact prescribing performance. Practices on the network edge with better information access show improved prescribing, while highly connected practices may perform worse.

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Area of Science:

  • Health Services Research
  • Social Network Analysis
  • Medical Practice Management

Background:

  • Polypharmacy in aging populations incurs significant costs.
  • Physician social networks influence prescribing behavior.
  • Optimizing prescribing is crucial for patient outcomes and healthcare economics.

Purpose of the Study:

  • To analyze the association between physician practice network connectedness and prescribing performance.
  • To investigate how social relationships among physicians affect medication appropriateness for seniors.

Main Methods:

  • Social network analysis mapped physician practices based on shared patients.
  • Prescribing performance was measured by inappropriate or missed medications for patients over 65 using the FORTA algorithm.
  • Negative binomial regression models assessed the relationship between network centrality measures and prescribing performance, controlling for covariates.

Main Results:

  • Network connectedness (degree, betweenness, eigenvector centrality) was significantly negatively associated with prescribing performance.
  • Physician practices with higher network centrality exhibited poorer prescribing outcomes.
  • Sensitivity analyses confirmed the robustness of these findings.

Conclusions:

  • Physician practice prescribing performance is linked to peer connections and network position.
  • Practices at the network periphery with access to novel information demonstrate better prescribing.
  • Highly connected practices in isolated networks are associated with suboptimal prescribing.