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Artificial Intelligence Approaches to Assessing Primary Cilia
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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

Clinical and Translational Science
|August 8, 2013
PubMed
Summary
This summary is machine-generated.

Qualitative evaluation using appreciative inquiry (AI) identified key features for successful Clinical and Translational Science Award (CTSA) infrastructure transformation. Open communication, proactive collaboration, and milestone achievement are crucial for improving health through research.

Keywords:
appreciative inquiryclinical translational scienceorganizational changequalitative evaluationresearch

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Area of Science:

  • Translational science
  • Health services research
  • Organizational development

Background:

  • Clinical and Translational Science Award (CTSA) evaluators identify change processes for research infrastructure and health improvement.
  • Qualitative evaluation complements quantitative measures but is under-utilized in CTSA evaluations.

Purpose of the Study:

  • To implement and assess a qualitative evaluation approach using appreciative inquiry (AI) for CTSA infrastructure transformation.
  • To identify critical features for successful CTSA infrastructure transformation.

Main Methods:

  • The Clinical and Translational Science Institute of Southeast Wisconsin implemented a longitudinal qualitative evaluation using appreciative inquiry (AI).
  • AI focused on identifying critical success factors for research infrastructure development.

Main Results:

  • Three critical features for CTSA infrastructure transformation success were identified: open communication, proactive collaboration, and milestone attainment.
  • Findings align with Bolman & Deal's four hallmarks of successful organizations: structural, political, human resource, and symbolic.

Conclusions:

  • Qualitative evaluation, specifically AI, effectively illuminates the progression of change features in CTSA-funded organizations.
  • These features are essential for creating multi-institutional infrastructures that translate laboratory discoveries into clinical treatments.