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3560 Using Research Performance Progress Report data to Explore CTSI-Stakeholder Engagement through Network Analysis
- Elizabeth Wayman, Eric P. Rubinstein, Camille Anne Martina, Ann Marie Dozier
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- Journal:
- Journal of Clinical and Translational Science / Volume 3 / Issue s1 / March 2019
- Published online by Cambridge University Press:
- 26 March 2019, p. 100
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- Article
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OBJECTIVES/SPECIFIC AIMS: To develop a social network model of collaborations within and external to the University of Rochester Medical Center (URMC) CTSI using data from the annual Research Performance Progress Report (RPPR) as well as other sources, to provide longitudinal evaluation of the CTSI’s engagement with key stakeholder groups. METHODS/STUDY POPULATION: The annually submitted RPPR follows a specific format with well-defined sections. The Highlights, Milestones and Challenges Report includes areas in which CTSI function leaders provide details about program integration and innovation, including collaborations with other functions or external groups. The Highlights, Milestones and Challenges Report was qualitatively coded to identify function-collaborator dyads. Each entity in the dyad became a node in the network. Nodes were connected by edges named by the dyads. The network included two types of nodes. The first were CTSI internal functions/programs, i.e. the entities that submitted RPPR sections and formed an interconnected sub-network. The second type of nodes were entities external to the CTSI (collaborators, internal or external to the CTSI site). These entities were named by functions submitting RPPR narratives. External nodes with similar meanings were consolidated. Duplicate edges were removed. CTSI-external nodes were grouped into five stakeholder categories: URMC, University of Rochester (UR), community, other CTSA institutions, CTSA consortium. Thus, these nodes were connected to the CTSI internal nodes, but not to each other. A second source of collaboration data was function-reported internal metrics. As part of the internal metric data collection, functions list partners who play a role in improving metric data or who are responsible for providing data. Partners identified in the internal metrics data, but not specified in the RPPR, were added to the network. RESULTS/ANTICIPATED RESULTS: Twenty-three internal CTSI functions submitted an RPPR and represent the CTSI internal nodes. Internal CTSI functions identified 235 collaborations (edges): 125 collaborations with other CTSI internal functions, 57 collaborations with URMC entities, 14 with UR entities, 15 with the external community, 15 with other institutions (CTSA hubs and other universities), and 9 with CTSA consortium entities. Thirty-eight of the collaborations were identified in the internal metrics partners section. In total, the network comprised 104 nodes. Graph density was.022 for full network and.21 for the CTSI internal sub-network. The global clustering coefficient, a measure of connectivity, for the CTSI internal sub-network was.252. DISCUSSION/SIGNIFICANCE OF IMPACT: The RPPR provides an underutilized source of data for annually repeated analyses of internal and external CTSI collaborations and is a way to enhance use of this routinely collected information. Analyses of the network yield metrics for measuring CTSI reach and impact on stakeholder groups over time. For example, measures such as number of nodes representing entities external to CTSI and average vertex degree of the CTSI Internal nodes track aspects of CTSI collaborations. Visualizations using different layouts or highlighting different sub-networks provide a representation of CTSI engagement with the communities of stakeholders as well as insights to relationships between functions, regions of collaboration, and areas of gaps. These data also provide an important new mechanism to engage the CTSI leadership and function leads in understanding how their work contributes to the overall network and synergies they have with each other.
3566 Longitudinal analysis of research collaborations and emerging networks
- Ann Marie Dozier, Elizabeth Wayman, Camille Anne Martina, Nicole O’Dell, Eric P. Rubinstein, Thomas T Fogg
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- Journal:
- Journal of Clinical and Translational Science / Volume 3 / Issue s1 / March 2019
- Published online by Cambridge University Press:
- 26 March 2019, pp. 132-133
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- Article
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- You have access Access
- Open access
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OBJECTIVES/SPECIFIC AIMS: To longitudinally track emerging research collaborations and assess their development and productivity. METHODS/STUDY POPULATION: In four administrations (2011, 2013, 2015, 2017), all full- and part-time University of Rochester Medical Center faculty received an email invitation to complete a research collaborators survey. Respondents indicated whether they were involved in research, and if involved in research, identified collaborators from a drop-down list of investigators in the institution. Space was provided for write-ins. Full- and part-time status, faculty rank, and departmental affiliation was associated with each investigator. Grant data were obtained from a grant management database maintained by the institution’s Office of Research and Project Administration. Grant data included all submissions (funded and not funded), award number, award effective data, award final expiration date, funding amounts, principal investigator and co-investigators. Using Mathematica SNA software, for each year we identified collaborator dyads (including their characteristics such as inter/intradepartmental; investigator characteristics) and networks (e.g. size, density). RESULTS/ANTICIPATED RESULTS: On average, 1800 (range 1730-2034) full- and part-time faculty received email invitations to complete the survey. An average of 403 respondents (range 385-441) completed the survey each administration. While the response rate seems low, the survey was distributed to every faculty member regardless of their primary appointment. Thus it included a large number of individuals whose role is exclusively clinical. Grant data included 4429 awards received between 2011 and 2018, involving 1395 investigators as principal or co-investigators. Survey respondents naming collaborators ranged from 233 to 280 (average 257) with 1594 to 2265 (average 1988) collaborations named each year. Overall density increased from.0204 in 2011 to.0342 in 2017. Density within the group of female investigators increased from.0219 in 2011 to.0412 in 2017. Within the group of male investigators, density increase from.0226 to.0333 in the same time span. Analysis by rank, changes over time and those with grant funding is underway. DISCUSSION/SIGNIFICANCE OF IMPACT: This methodology captured a consistent number of collaborations over an 8 year period. Analyses reveal network growth over time and of increasing heterogeneity (by gender). Analyzing research networks overtime provides an important metric to assess how research networks evolve and devolve and the characteristics of those that grow or stagnate. Further these analyses can demonstrate the impact of support provided to networks or teams by the CTSI, department or other institutional mechanism.