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Referral paths in the U.S. physician network.

Chuankai An1, A James O'Malley2, Daniel N Rockmore1,3,4

  • 11Department of Computer Science, Dartmouth College, Hanover, 03755 NH USA.

Applied Network Science
|March 7, 2019
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Summary
This summary is machine-generated.

Analyzing patient referral paths reveals network patterns that can predict cardiovascular treatment and outcomes. This network science approach optimizes patient referrals for better healthcare efficiency and results.

Keywords:
Big dataHealth record analysisNetwork sciencePredictive modelingSocial network analysis

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Area of Science:

  • Healthcare Systems Analysis
  • Network Science
  • Cardiovascular Medicine

Background:

  • Patient referral paths are crucial for understanding healthcare system dynamics.
  • Previous analyses have not fully leveraged referral path data for outcome prediction.

Purpose of the Study:

  • To analyze millions of patient referral paths from 2006-2011.
  • To relate referral path characteristics to cardiovascular treatment and patient outcomes.
  • To explore the potential of network science in optimizing healthcare referrals.

Main Methods:

  • Analysis of patient referral paths and healthcare system interactions.
  • Construction of referral networks based on physician encounters.
  • Correlation of referral path features with Acute Myocardial Infarction (AMI) treatment and outcomes.
  • Utilizing tree-based predictive models.

Main Results:

  • Identified significant referral path features that predict patient treatment and medical outcomes.
  • Demonstrated stronger correlations between referral path metrics and numerical treatment outcomes.
  • Highlighted specific referral path patterns with predictive power for cardiovascular care.

Conclusions:

  • Referral path analysis using network science can optimize patient referrals.
  • This approach has the potential to improve cardiovascular treatment outcomes.
  • Network science offers a pathway to more efficient utilization of medical resources.