Increasing Equity Through Technology: A Comparison of Opinion Leader Identification Methods in Primary Care.

Abstract

Identifying low-cost implementation strategies to facilitate the uptake of technological innovations can help low-resource community clinics mitigate health disparities. Using a social network approach to identify organizational opinion leaders (OLs) can facilitate the adoption of innovations. To fill knowledge gaps related to alternative methods of identifying OLs, we identify and compare OLs in a low-resource community clinic using theoretically based techniques using Phi correlations and a binary logistic regression. Results showed that OLs identified through 3 out of 4 non-network identification methods (self-identification, positional, and staff selection) were significantly positively correlated with OLs identified using a social network approach. In addition, combining positional and staff selection methods was also found to be significantly associated with OLs identified using the social network approach. Implications for public health include the potential for non-network identification techniques to identify OLs to increase the uptake of technological innovations in low resource community clinics.