Good relations: the use of a relational database for large-scale data analysis

Area of Science:

• Nursing Research
• Data Analysis
• Health Informatics

Background:

• Analyzing large nursing datasets presents challenges in integrating diverse data types.
• Existing statistical packages may not fully support the complexities of nursing research data.

Purpose of the Study:

• To report on the analysis of a large UK nursing practice dataset.
• To devise and evaluate a method for analyzing and integrating quantitative and qualitative nursing data.
• To assess the utility of an inexpensive relational database for nursing research.

Main Methods:

• Utilized a relational database for analyzing a large dataset of nursing practice in the UK.
• Employed a mixed-methods approach combining quantitative and qualitative data analysis.
• Developed a method to link free-text and structured questionnaire data.

Main Results:

• The relational database proved effective for managing and analyzing combined data types.
• Key advantages included ease of use for nursing specialists, free-text analysis, and data integration.
• The tool facilitated exploratory analysis and hypothesis testing during the research process.

Conclusions:

• Relational databases offer significant advantages over conventional statistical packages for nursing research.
• The chosen database facilitated flexible, integrated analysis of complex nursing data.
• This approach enhances data control and analytical capabilities for domain specialists.