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A Winning Strategy On Data Quality - Putting the Right Pieces Together

A Winning Strategy On Data Quality - Putting the Right Pieces Together. May 17th, 2011 | Beijing, China. Highlights. The quality control system on data management in clinical trials What are the challenges Building sustainable organizational capability of quality assurance.

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A Winning Strategy On Data Quality - Putting the Right Pieces Together

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  1. A Winning Strategy On Data Quality -Putting the Right Pieces Together May 17th, 2011 | Beijing, China

  2. Highlights • The quality control system on data management in clinical trials • What are the challenges • Building sustainable organizational capability of quality assurance www.diahome.org

  3. Quality Control System on Data Management • People: • Knowledge • Experience • Competency • Capacity • Compliance • Environment: • Regulations • ICH E6/E2A/E8 • 21 CFR Part 11/50/312 • European Union Clinical Trial Directive Data Quality in Clinical Trials • Technology: • Systems • Applications • Software / Hardware • Methodology • Media • Infrastructure: • Quality standard • Implementation guidelines • Administrative structure and resource • Metrics: • Key Performance Indicators • Evaluations • Report of metrics • Control System: • SOPs and Processes • QC / QA • Audit • Inspection

  4. Quality Control System on Data Management Design of Protocol, CRF, and Database Pre-defined templates to ensure what data to be collected and consistent format of data, such as CDISC, 21CFR11, ICH E6, and company used Data Standards to ensure the consistency of data quality standard. Regulations, Industry Guidance, SOPs & Processes Data Flow Data Flow Activities Document is to define where data is located; how data is transferred; time frame for actions; and Task Owners Metrics, etc. to ensure the timeliness of data Data Collection A series of processes, such as CRF Completion Requirement; Data Entry Guidelines, Source Document Verification Procedures; and Personal Data Protection Guidelines, etc. to ensure data completeness & accuracy • - Discrepancies management: Data Handling Conventions (Self-evident • Corrections); Data Quality Specifications for edit checks • Coding conventions: using international implemented dictionaries to • categorize medical or treatment terms • - e-data reconciliation process: for batch loaded data from other databases, • such as central lab data, PK/PD data, etc. • - SAE Reconciliation guideline: to ensure SAE information are consistent in • both safety and project data bases • - Manual reviews by defining templates of data listings document to ensure • complete, accuracy and reliable data Data Management Data QC Data Quality Control Plan is to define the process of how the in-progress data quality control is conducted, such as which system/database is compared, when, how, by whom, etc. Access control and audit trail for each change of patient data to ensure the reliability. Access Control & Audit Trail

  5. Highlights • The quality control system on data management in clinical trials • What are the challenges • Building sustainable organizational capability of quality assurance Drug Information Association www.diahome.org 5

  6. Some statistics QUALITY Drug Information Association www.diahome.org 6

  7. Some statistics Drug Information Association www.diahome.org 7 TYPES OF ERRORS Errors of Ignorance Errors of Ineptitude

  8. The challenges • Do we have the right persons in place? • Do we have a good system in place? • Do we have right metrics to make the data quality become visible and comparable? • How to build a sustainable capability of quality assurance in a new and fast expanding organization? • What are the key success factors of high quality data delivery? Drug Information Association www.diahome.org 8

  9. Highlights • The quality control system on data management in clinical trials • What are the challenges • Building sustainable organizational capability of quality assurance Drug Information Association www.diahome.org 9

  10. Building sustainable organizational capability of quality assurance • Manage BEHAVIORS • in addition to • manage RESULTS Drug Information Association www.diahome.org 10

  11. Building sustainable organizational capability of quality assurance 1. Plan. Identify the factors critical to quality with metrics to measure them. Identify the high-risk processes with quality management plans to mitigate these risks 2. Conduct. Conduct Data Management Act Plan 3. Check. Use tools and risk metrics to monitor performance 4. Act. Perform root cause analysis, take corrective and preventitive actions, and modify mitigating factors, if necessary Learning Cycle Check Do “Closed Loop System” Pfizer Confidential

  12. Building sustainable organizational capability of quality assurance Check Pfizer Confidential

  13. Building sustainable organizational capability of quality assurance DHC TMF Check Pfizer Confidential

  14. Building sustainable organizational capability of quality assurance Check The little things make all the differences. Pfizer Confidential

  15. Summary • Quality control system are essential to ensuring data quality in clinical trials • Quality assurance is a capability both to individuals and organizations, which is trainable, manageable, and sustainable • Build the organizational behavior of continuous improvement on data quality is the key success factor for a new data center in China Drug Information Association www.diahome.org 15

  16. Thank You Drug Information Association www.diahome.org 16

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