Related Experiment Video
Updated: May 9, 2026

Artificial Intelligence Approaches to Assessing Primary Cilia
Published on: May 1, 2021
Using AI to understand key success features in evolving CTSAs
Jennifer D Kusch1, David A Nelson, Deborah Simpson
1Medical College of Wisconsin, Clinical and Translational Science Institute of Southeast Wisconsin, Education, Milwaukee, Wisconsin, USA. jkusch@mcw.edu
Abstract:
A vital role for Clinical and Translational Science Award (CTSA) evaluators is to first identify and then articulate the necessary change processes that support the research infrastructures and achieve synergies needed to improve health through research. The use of qualitative evaluation strategies to compliment quantitative tracking measures (e.g., number of grants/publications) is an essential but under-utilized approach in CTSA evaluations. The Clinical and Translational Science Institute of Southeast Wisconsin implemented a qualitative evaluation approach using appreciative inquiry (AI) that has revealed three critical features associated with CTSA infrastructure transformation success: developing open communication, creating opportunities for proactive collaboration, and ongoing attainment of milestones at the key function group level. These findings are consistent with Bolman & Deal's four interacting hallmarks of successful organizations: structural (infrastructure), political (power distribution; organizational politics), human resource (facilitating change among humans necessary for continued success), and symbolic (visions and aspirations). Data gathered through this longitudinal AI approach illuminates how these change features progress over time as CTSA funded organizations successfully create the multiinstitutional infrastructures to connect laboratory discoveries with the diagnosis and treatment of human disease.
Related Concept Videos
Statistical Analysis System (SAS)
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
Cancer Survival Analysis
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Comparing the Survival Analysis of Two or More Groups
Multiple Comparison Tests
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...

