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DIGITAL SOCIAL NETWORK ANALYSIS AS A STRATEGY FOR UNDERSTANDING VARIATION IN THE PARTICIPATION OF PATIENTS IN HEALTHCARE QUALITY IMPROVEMENT
  1. Shannon Provost1,
  2. Peter Gloor2,
  3. Michael Seid3,
  4. Peter Margolis3
  1. 1Boston College, United States
  2. 2MIT Center for Collective Intelligence, United States
  3. 3Cincinnati Children's Hospital Medical Center, United States

Abstract

Background Healthcare improvement work benefits from diverse stakeholder participation. Great strides are being made towards formal collaborative relationships with patients and their caregivers. But how will we know if these overtures evolve into true partnerships? Reliable methods for tracking participation are needed to understand and enumerate how contributions of patients and families may impact costs, care, and outcomes.

Objectives We share an innovative approach to evaluating participation in healthcare improvement initiatives. Social network analysis (SNA) offers insight around the extent to which patient involvement on improvement teams is authentic and comparable to that of conventional contributors (e.g., clinicians and professional researchers).

Methods Using digital archives of email correspondence from 24 participants in a design project for pediatric chronic illness care, we generated email-network graphs over 19 months (January 2013–July 2014) to visually identify collaborators, measure communication behaviors, and quantify their prominence within the group network. We used scatterplots and Shewhart charts to compare network-based measures for patients and parents over time and relative to other participants.

Results Longitudinal email-based SNA provided evidence of a qualitative trend of increased patient and parent participation throughout the project. X-bar charts showed common cause variation in centrality measures for patients/parents alongside clinicians and researchers, evidence of similar positioning within the group network as well as comparable levels of communication.

Conclusions SNA is a reliable and relatively unobtrusive method to detect and monitor participation in collaborative work groups. Next, we explore how this approach could inform design and management of improvement efforts that meaningfully involve more patients and their caregivers.

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