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Data Quality and Diversity in Health Care and Health Research
Solveig Bünz1, Sonja Harkener1, Jürgen Stausberg1
1Institute for Medical Informatics, Biometry and Epidemiology, Faculty of Medicine, University Duisburg-Essen, Essen, Germany.
Studies in Health Technology and Informatics
|May 17, 2025
Summary
Poor data quality in health systems can negatively impact diversity, equity, and inclusion. Addressing data quality is crucial for fair health research and care, especially concerning age, race, sex, gender, and social status.
Area of Science:
- Health Informatics
- Health Services Research
- Data Science
Background:
- Data-driven health systems are increasingly important.
- Insufficient data quality poses risks to diversity, equity, and inclusion (DEI).
- Understanding the link between data quality and DEI is critical for equitable health outcomes.
Purpose of the Study:
- To identify and analyze evidence on the relationship between data quality and diversity in health research and care.
- To highlight risks to DEI stemming from poor data quality.
- To inform best practices for data collection and management in health.
Main Methods:
- A literature review was conducted to find studies on data quality and diversity.
- A descriptive analysis was performed on thirteen selected studies.
- The analysis focused on aspects of age, race and ethnicity, sex and gender, and social status.
Main Results:
- Risks to DEI were identified, including misclassifications and missing data.
- Broad categorization and lack of cultural awareness negatively impact data quality.
- Specific concerns were noted across age, race, ethnicity, sex, gender, and social status.
Conclusions:
- Ensuring data quality is essential for maintaining diversity, equity, and inclusion in health.
- Consideration of DEI risks must be integrated into the planning and management of health data.
- Improved data quality practices are needed for both health research and health care settings.
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