title: Diffusion of Innovations model helps interpret the comparative uptake of two methodological innovations: co-authorship network analysis and recommendations for the integration of novel methods in practice.
abstract: OBJECTIVE
  The objective of this study was to characterize the diffusion of methodological innovation.
  
  
  METHODS
  Comparative case study analysis of the diffusion of two methods that summarize confounder information into a single score: disease risk score (DRS) and high-dimensional propensity score (hdPS). We completed systematic searches to identify DRS and hdPS papers in the field of pharmacoepidemiology through to the end of 2013, plotted the number of papers and unique authors over time, and created sociograms and animations to visualize co-authorship networks. First and last author affiliations were used to ascribe institutional contributions to each paper and network.
  
  
  RESULTS
  We identified 43 DRS papers by 153 authors since 1981, reflecting slow uptake during initial periods of uncertainty and broader diffusion since 2001 linked to early adopters from Vanderbilt. We identified 44 hdPS papers by 147 authors since 2009, reflecting rapid and integrated diffusion, likely facilitated by opinion leaders, early presentation at conferences, easily accessible statistical code, and improvement in funding. Most contributions (87% DRS, 96% hdPS) were from North America.
  
  
  CONCLUSIONS
  When proposing new methods, authors are encouraged to consider innovation attributes and early evaluation to improve knowledge translation of their innovations for integration into practice, and we provide recommendations for consideration.
authors.affiliation: Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario M5S 3M2, Canada. Electronic address: s.cadarette@utoronto.ca.
authors.forename: Suzanne M
authors.initials: SM
authors.lastname: Cadarette
authors.affiliation: Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario M5S 3M2, Canada.
authors.forename: Joann K
authors.initials: JK
authors.lastname: Ban
authors.affiliation: Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario M5S 3M2, Canada.
authors.forename: Giulia P
authors.initials: GP
authors.lastname: Consiglio
authors.affiliation: Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario M5S 3M2, Canada.
authors.forename: Cody D
authors.initials: CD
authors.lastname: Black
authors.affiliation: Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario M5S 3M2, Canada.
authors.forename: David
authors.initials: D
authors.lastname: Dubins
authors.affiliation: Department of Sociology, University of Toronto, 725 Spadina Avenue, Toronto, Ontario M5S 2J4, Canada.
authors.forename: Alexandra
authors.initials: A
authors.lastname: Marin
authors.affiliation: Leslie Dan Faculty of Pharmacy, University of Toronto, 144 College Street, Toronto, Ontario M5S 3M2, Canada.
authors.forename: Mina
authors.initials: M
authors.lastname: Tadrous
mesh_terms: D001319:Authorship; D015706:Bibliometrics; D004059:Diffusion of Innovation; D006801:Humans; D057216:Propensity Score; D011643:Publishing / Q000706:statistics & numerical data*
keywords: Bibliometrics; Diffusion of innovation; Disease risk score; Methodological innovation; Pharmacoepidemiology; Propensity score; Social networks