ASPIRE and STRIVE: Two proposed models to inform the design of network implementation interventions in healthcare organizations
Stephanie Glegg, Anita Kothari, Laura Nimmon, Liisa HolstiBackground: Knowledge translation (KT) is a social process aimed at moving evidence into action in healthcare. KT includes dissemination, barrier assessments, collaborative planning, implementation, and evaluation. Social factors are documented drivers of evidence use, while socially-based KT interventions (e.g. opinion leaders; knowledge brokers), have gained increasing attention in implementation science. A network perspective assists in recognizing socially-based interventions as valued supports for implementation within organizations. Social network analysis (SNA) offers a unique and more comprehensive means of informing the design of KT interventions compared to traditional individual or contextual lenses.
Aim: To identify network-specific KT interventions for use within healthcare organizations, from the perspectives of researchers, clinicians, leaders and KT support personnel.
Methods: This presentation reports on qualitative findings from a mixed-methods SNA descriptive case study. An online SNA survey within a single paediatric healthcare organization enabled the mapping of individuals involved in KT activities. Theoretical sampling guided recruitment of 29 interview participants representing diverse clinical programs, professional roles, and network positions (high, average, and low centrality). Interviews gathered insights about perceptions of the network, key individuals, roles, barriers and supports for the phases of the Knowledge-to-Action Implementation Framework, as well as interventions to strengthen the network, the latter of which are reported here. An orientation to network properties and their implications for KT, and the use of visual tools generated from organizational network data afforded participants a network perspective that was present in interviews.
Relational data was entered into an adjacency matrix and imported into UCINet to identify structural brokers (via betweenness centrality) and key actors (via in/outdegree centrality). Netdraw was used to generate velum ego-network graphs of interview participants to overlay on whole network graphs. Thematic analysis of qualitative data followed LeCompte’s six-phased iterative approach.
Results: Network-relevant themes emerging from the data were arranged into two proposed models. Specific interventions from each theme will be presented.
The ASPIRE model’s themes categorize individual-level interventions to support KT: (1) Ask (leverage alters to access knowledge, resources, support); 2) Share (use ties to share same); 3) Participate (take collaborative implementation action); 4) Inspire (stimulate change by alters); 5) Relate (strengthen existing ties to foster action); and 6) Expand (reflect on and extend own abilities, reach and influence).
The STRIVE model presents organizational-level interventions by theme: 1) Systematize (establish mechanisms to foster network development); 2) Transmit (communicate about KT values, supports, activities); 3) Resource (coordinate access to evidence and KT resources); 4) Invest (build KT capacity, retain staff, and implement support roles/programs); 5) Value (foster a culture of KT); and 6) Evaluate (network structure, barriers, needs, and KT activities).
Conclusions: Our novel qualitative approach generated two proposed models to inform the design and testing of network implementation interventions. These models advance implementation science by emphasizing the value of SNA in examining KT. A network lens provided a novel conceptualization of organizational and individual KT interventions by highlighting social mechanisms by which KT processes are enacted. The identified interventions also provide a foundation for assessing network-specific barriers (e.g. inequities) and strengths (e.g. trust).