Best Practices / Research Oral Abstract

Social Network Analysis (O010)

John Kues (University of Cincinnati); Maureen Doyle-Scharff (Pfizer); Jann Balmer (University of Virginia)

Purpose

As the importance of systems is recognized in healthcare delivery, the need to assess and change systems as part of continuous professional development is increasingly apparent. Integration of care is built around networks of providers with varying degrees of communication and influence. In order to include human systems and networks in performance improvement models it is critical that these systems be measurable. Effective tools for examining systems are required for both assessing and changing systems.

Methods

A sample of 25 participants and faculty from the 2011 Alliance Leadership Workshop listed individuals with whom they had worked in the past year. Snowball sampling was used to identify a second cohort who also identified collaborators. Organization type was also coded for each individual.

Results

Social network analysis, using NodeXL, was conducted on the contacts from the initial sample of participants. It revealed 646 unique individuals and 1,339 connections. The average distance between any two individuals was 3.1 and the maximum distance was 5. Analyses are ongoing with the second dataset. Excluding the original 25 participants, an additional 10-15 individuals were identified as central to networks of CME professionals. Small constellations of key individuals were found to account for most of the connections in the overall network.

Conclusions

Social network analysis is an important tool for identifying key individuals within human systems and the overall organization of these systems. It can monitor planned system changes and can help inform the types of changes that are needed.