Whatever can go wrong, need not go wrong: Open Quality approach for epidemiology

Area of Science:

• Epidemiology
• Public Health
• Biostatistics

Background:

• Data quality is crucial for epidemiological study validity.
• Quality management principles are widely adopted in industry but less so in epidemiology.
• Existing quality assurance models (Juran, Donabedian, ISO 9000) offer potential for epidemiological application.

Purpose of the Study:

• To review and integrate established quality assurance models for epidemiology.
• To propose a novel, systematic, and flexible approach for quality assurance in epidemiological studies.
• To introduce a practical tool to support the implementation of this approach.

Main Methods:

• Review of Juran, Donabedian, and ISO 9000 quality assurance models.
• Development of the 'Open Quality' approach, integrating elements from reviewed models.
• Proposal of a structured process for defining quality attributes, failure modes, and control strategies.
• Introduction of an 'Open Quality' tool for practical application.

Main Results:

• The Open Quality approach systematically integrates planning, control, and verification processes.
• It adapts industrial quality principles to the specific needs of epidemiological research.
• The proposed tool facilitates the definition of quality attributes, failure modes, preventive strategies, and corrective actions.
• The approach offers a flexible framework for enhancing data quality and study validity.

Conclusions:

• The Open Quality approach provides a structured and adaptable framework for quality assurance in epidemiology.
• Integrating industrial quality models can significantly improve the validity and reliability of epidemiological studies.
• The developed tool supports the practical implementation of enhanced quality assurance in research settings.