What should systems and processes for data capture and management ensure?

• A. They should be scalable and feature-rich, regardless of risk.
• B. They should be ad hoc and improvised.
• C. They should be fit for purpose, capture required data, and be proportionate to risks and data importance.
• D. They should be outsourced to third parties.

Answer: (C)

Systems and processes for data capture and management must be fit for purpose, capture only what is needed, and apply controls that match the level of risk and the importance of the data. This means designing the system to support the study’s specific data requirements and safety needs, with mechanisms to ensure data are accurate, complete, and traceable. The amount of rigor should scale with risk: critical safety data and key efficacy endpoints receive stronger controls (validation rules, audit trails, access restrictions, data quality checks), while less critical data can be managed with proportionally lighter, yet still compliant, controls. This balanced, risk-based approach protects data integrity and regulatory compliance without unnecessary complexity.

Choosing an ad hoc or improvised system would undermine data integrity and traceability. A system that is feature-rich regardless of risk may introduce unnecessary complexity and cost. Outsourcing can be part of the solution, but it does not by itself guarantee proper data capture and management; controls and oversight must align with the study’s risk profile.