Conducting requirements analyses for research using routinely collected health data: a model driven approach

Area of Science:

• Health Informatics
• Software Engineering in Medicine
• Biomedical Data Science

Background:

• Medical research increasingly necessitates integrating data from disparate sources.
• Requirements analysis is standard in software engineering but underreported in biomedical literature.
• Generic approaches for linking heterogeneous health data are lacking.

Purpose of the Study:

• To develop a standardized methodology for requirements analysis in multi-source health data research.
• To address the gap in published generic approaches for linking heterogeneous health data.

Main Methods:

• A literature review was conducted.
• A consensus process was employed to define requirements modeling for multi-source research.
• The i-ScheDULEs methodology was developed, incorporating indexing and rich picture creation.

Main Results:

• The i-ScheDULEs methodology includes indexing and rich picture creation for research studies.
• Reference models of increasing complexity were developed: Data Flow Diagrams (DFD) for data requirements.
• Unified Modeling Language (UML) use case diagrams for study-specific and governance needs.
• Business Process Models (BPMN) were utilized for process requirements.

Conclusions:

• The developed requirements and models should be integrated into research study protocols.
• Standardized requirements analysis can enhance the linkage of heterogeneous health data.
• This approach facilitates more robust and reproducible medical research.