Disseminating educational innovations in health care practice: training versus social networks

Soc Sci Med. 2010 May;70(10):1509-17. doi: 10.1016/j.socscimed.2009.12.035. Epub 2010 Feb 12.


Improvements and innovation in health service organization and delivery have become more and more important due to the gap between knowledge and practice, rising costs, medical errors, and the organization of health care systems. Since training and education is widely used to convey and distribute innovative initiatives, we examined the effect that following an intensive Teach-the-Teacher training had on the dissemination of a new structured competency-based feedback technique of assessing clinical competencies among medical specialists in the Netherlands. We compared this with the effect of the structure of the social network of medical specialists, specifically the network tie strength (strong ties versus weak ties). We measured dissemination of the feedback technique by using a questionnaire filled in by Obstetrics & Gynecology and Pediatrics residents (n=63). Data on network tie strength was gathered with a structured questionnaire given to medical specialists (n=81). Social network analysis was used to compose the required network coefficients. We found a strong effect for network tie strength and no effect for the Teach-the-Teacher training course on the dissemination of the new structured feedback technique. This paper shows the potential that social networks have for disseminating innovations in health service delivery and organization. Further research is needed into the role and structure of social networks on the diffusion of innovations between departments and the various types of innovations involved.

MeSH terms

  • Age Factors
  • Attitude of Health Personnel
  • Clinical Competence
  • Diffusion of Innovation*
  • Education, Medical, Continuing* / methods
  • Female
  • Humans
  • Information Dissemination / methods*
  • Male
  • Models, Theoretical
  • Netherlands
  • Physicians / psychology
  • Physicians / statistics & numerical data
  • Regression Analysis
  • Sex Factors
  • Social Support*