Adam G Dunn1, Blanca Gallego, Enrico Coiera. 1. Centre for Health Informatics, Australian Institute of Health Innovation, University of New South Wales, Sydney, NSW 2052, Australia. a.dunn@unsw.edu.au
Abstract
OBJECTIVE: To measure the relative influence that industry authors have on collaborative research communities and evidence production. STUDY DESIGN AND SETTING: Using 22 commonly prescribed drugs, 6,711 randomized controlled trials (RCTs), and 28,104 authors, 22 collaboration networks were constructed and analyzed. The directly industry-affiliated (DIA) authors were identified in the networks according to their published affiliations. Measures of influence (network centrality) and impact (citations) were determined for every author. Network-level measures of community structure and collaborative preference were used to further characterize the groups. RESULTS: Six percent (1,741 of 28,104) of authors listed a direct affiliation with the manufacturer of a drug evaluated in the RCT. These authors received significantly more citations (P<0.05 in 19 networks) and were significantly more central in the networks (P<0.05 in 20 networks). The networks show that DIA authors tend to have greater reach in the networks and collaborate more often with non-DIA authors despite a preference toward their own group. Potential confounders include publication bias, trial sizes, and conclusions. CONCLUSIONS: Industry-based authors are more central in their networks and are deeply embedded within highly connected drug research communities. As a consequence, they have the potential to influence information flow in the production of evidence. Copyright Â
OBJECTIVE: To measure the relative influence that industry authors have on collaborative research communities and evidence production. STUDY DESIGN AND SETTING: Using 22 commonly prescribed drugs, 6,711 randomized controlled trials (RCTs), and 28,104 authors, 22 collaboration networks were constructed and analyzed. The directly industry-affiliated (DIA) authors were identified in the networks according to their published affiliations. Measures of influence (network centrality) and impact (citations) were determined for every author. Network-level measures of community structure and collaborative preference were used to further characterize the groups. RESULTS: Six percent (1,741 of 28,104) of authors listed a direct affiliation with the manufacturer of a drug evaluated in the RCT. These authors received significantly more citations (P<0.05 in 19 networks) and were significantly more central in the networks (P<0.05 in 20 networks). The networks show that DIA authors tend to have greater reach in the networks and collaborate more often with non-DIA authors despite a preference toward their own group. Potential confounders include publication bias, trial sizes, and conclusions. CONCLUSIONS: Industry-based authors are more central in their networks and are deeply embedded within highly connected drug research communities. As a consequence, they have the potential to influence information flow in the production of evidence. Copyright Â