Data management
Standard operating procedures for data management support consistent project execution.
03 / QUALITY MANAGEMENT
Quality management system
DataSage Tech has established and implements SOPs and a quality management system covering data management and statistical analysis, supporting consistent project execution and delivery.
SOP: Standard Operating Procedure
SOP coverage
Statistical analysis
Standard operating procedures for statistical analysis support consistent analysis and delivery.
Quality management priorities
Quality requirements, working references and deliverables are defined around key project activities. Specific controls are agreed according to the protocol, study risks and service scope.
01
Define the foundation
Procedures & responsibilities
01SOPs & document control
Focus on applicable procedures, project plans and templates, with clear versions, approval requirements and reasons for change.
02Responsibilities & training
Clarify execution, review and communication responsibilities, and identify training needs for the protocol, procedures and tools.
02
Apply project controls
Risks & review
03Risk & quality planning
Identify risks affecting critical data, study endpoints and deliverables; agree review milestones and the scope of checks.
04Process checks & output review
Focus on data checks, coding consistency and traceability between analysis data and statistical outputs, with review methods agreed for the study.
03
Review & deliver
Actions & records
05Issue handling & improvement
Consider impact, causes, actions and follow-up when addressing quality issues, and use project feedback to inform process improvement.
06Data protection & archiving
Agree requirements for data access, transfer, delivery and retention, with attention to confidentiality and complete working records.
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