An Architecture for Continuous Data Quality Monitoring in Medical Centers

Area of Science:

• Medical Informatics
• Data Science
• Health Systems Engineering

Background:

• Data quality is critical in the medical domain.
• Frequent changes in medical requirements and data necessitate ongoing quality management.
• Existing systems may lack flexibility for domain expert adaptation.

Purpose of the Study:

• To develop a novel architecture for a sustainable medical data quality monitoring system.
• To enable domain experts to adapt monitoring specifications at runtime.
• To facilitate the integration of complex analyses into the data quality cycle.

Main Methods:

• Collaborative development with medical center managers.
• Design of a data quality monitoring system architecture.
• Implementation of a built-in rule system for runtime adaptation.
• Evaluation against the Total Data Quality Management (TDQM) methodology.

Main Results:

• The proposed architecture allows for dynamic adaptation of data quality rules by domain experts.
• Complex analytical methods can be seamlessly integrated into the monitoring process.
• The system's components align with the principles of the TDQM methodology.

Conclusions:

• The developed architecture provides a flexible and sustainable solution for medical data quality monitoring.
• Empowering domain experts with runtime adaptation capabilities enhances system relevance.
• The architecture supports continuous improvement of data quality in dynamic medical environments.