Data management in clinical research: Synthesizing stakeholder perspectives

Area of Science:

• Clinical research informatics
• Health data management
• Software engineering in healthcare

Background:

• Clinical research relies heavily on effective data management.
• Understanding the needs of diverse stakeholders is crucial for developing supportive technologies.
• Current data management tools may not fully meet the demands of modern clinical research.

Purpose of the Study:

• To assess data management needs in clinical research.
• To gather perspectives from researchers, software analysts, and developers.
• To identify gaps and opportunities in current clinical research software.

Main Methods:

• A mixed-methods approach combining content analysis and surveys.
• Sublanguage analysis applied to transcribed interviews with researchers.
• Development of survey questions based on a common sublanguage for all stakeholders.
• Synthesis of results using the common sublanguage to compare perceptions.

Main Results:

• Researchers expressed diverse needs, particularly for improved integration, interoperability, and participant engagement.
• Data integration was highly desired by researchers and analysts, while mobile technology was less desired.
• Disagreement existed on the desirability of data validation rules between researchers and analysts.
• Developers identified data integration and validation as most challenging to implement.

Conclusions:

• Clinical researchers view study execution, analysis, and quality control as strategic, yet lack adequate technological support.
• Data integration and validation software are vital but potentially expensive.
• Underappreciated features supporting workflow, collaboration, and engagement could be "easy successes" for software developers.