Building an evaluation infrastructure to capture process and progress within a Clinical and Translational Science...

Area of Science:

• Clinical and Translational Science
• Health Services Research
• Program Evaluation

Background:

• Effective management capacity is crucial for research institutes.
• Existing evaluation infrastructures often lack comprehensiveness, efficiency, and transparency.
• Standardizing measures and streamlining data collection are key challenges.

Purpose of the Study:

• To overhaul the evaluation infrastructure of Frontiers Clinical and Translational Science Institute.
• To develop a comprehensive, efficient, and transparent system for demonstrating research outputs and outcomes.
• To reduce the data entry burden for investigators and integrate continuous improvement processes.

Main Methods:

• Utilized the Utilization-Focused Evaluation Framework to develop logic models and identify appropriate metrics.
• Built an evaluation data platform within REDCap, integrating nine projects across multiple programmatic areas.
• Implemented a membership model using REDCap Dynamic SQL query fields and External Modules for tailored communication and data capture.
• Integrated data synchronization to a real-time dashboard for tracking outputs and outcomes.

Main Results:

• Increased workflow efficiency and streamlined continuous improvement communication since the platform's launch in Fall 2022.
• Standardized measures across program areas, reducing the data entry burden for investigators.
• Achieved comprehensive, efficient, and transparent demonstration of outputs and outcomes.

Conclusions:

• The developed evaluation platform significantly enhances management capacity and operational efficiency.
• The platform serves as a replicable model for other research hubs seeking to build robust evaluation plans.
• Integration of REDCap and a membership model proved effective for data management and process improvement.