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A study of physician collaborations through social network and exponential random graph
Shahadat Uddin1, Liaquat Hossain, Jafar Hamra
1Complex System Research Centre, The University of Sydney, Sydney NSW 2006, Australia. shahadat.uddin@sydney.edu.au
BMC Health Services Research
|June 28, 2013
Summary
Physician collaboration network density positively impacts hospital costs and readmissions, while betweenness centralisation reduces them. Understanding these structures can improve healthcare performance.
Area of Science:
- Healthcare Management
- Network Science
- Health Economics
Background:
- Physician collaboration is vital for effective patient care in hospitals.
- Understanding collaboration structures can optimize healthcare outcomes.
Purpose of the Study:
- To explore physician collaborations using social network analysis (SNA) and exponential random graph (ERG) models.
- To examine the impact of network measures on hospitalisation cost and readmission rates.
Main Methods:
- Mapping physician collaboration networks (PCN) from patient visit data.
- Applying SNA measures (density, centralisation) and ERG models.
- Utilising an Australian electronic health insurance claim dataset.
Main Results:
- PCN density positively correlates with hospitalisation cost and readmission rates.
- Betweenness centralisation negatively correlates with cost and readmissions.
- Degree centralisation negatively correlates with readmissions.
Conclusions:
- Collaboration structures significantly influence hospitalisation costs and readmission rates.
- Findings can inform guidelines for improving healthcare professional collaboration.
- Network analysis offers insights into optimizing healthcare delivery.
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