Data Management: Good Team Work is de sleutel tot succes! Gerald Ruiter Senior Data Manager
Topics Introduction Data Management Activities People Process Technology
Clinical Data Management: introduction Aim: obtain accurate results for any clinical trial Determined by quality of collected data
Clinical Data Management: introduction Clinical Data Managers are responsible for delivery of high quality, regulatory compliant clinical databases for regulatory submissions and publication of study results.
Good Data Management Practices Conduct trial conform GCP standards Follow the SOPs User training is essential CRF is most important instrument to acquire data Document everything that you do
Good Clinical Practice (GCP) Ensures that patient s rights have been protected Confidence in integrity of collected data and published results
SOPs: who is responsible for what defines workflow and when
Data Management Activities
Managing Clinical Data Data Acquisition Safety Database Administration IT Regulatory Quality Assurance
People Managing Clinical Data Process Technology
Managing Clinical Data - People Study Manager EDC vendor Medical Monitor Database Administrator CRA - SAS programmer/statistician - Drug Safety Officer Data Entry Operator (paper CRF or diaries)
Good communications skills (English: oral and written), and the ability to work collaboratively in (mostly international) clinical development teams Accurate Flexible Stress-Resistant Planner Clinical Data Manager Timelines (who, what, when?)
Common pitfall - Data Management is often dependent on input of other parties (e.g. review of DVP) - Timelines are mostly setup in advance and often fixed - Problem: the Data Manager involved in the final step gets the burden of the fixed timeline
Common pitfall Solution: make timelines interdependent and make clear agreements e.g.: final document available 5 working days after final comments have been received CRA should notify Data Manager in timely manner when monitor visit takes place and when a patient is ready for manual review (Why? Manual review of ecrf data takes time and usually a Data Manager works on more than 1 study; sometimes it is required to change priorities to ensure that queries are ready on time)
Managing Clinical Data - Process
Data Management activities (e)crf development Development of data management documents Database validation / UAT (screens/checks) Coordinate Data entry (questionnaires) Query processing Data coding Subject review: manual checks on ecrf data Lock data on subject level vs complete database lock
Data Management activities Clinquest Services STUDY SETUP STUDY CONDUCT STUDY CLOSE OUT
Data Management activities Clinquest Services Study Setup starts once final protocol becomes available
Study Setup Study protocol Data Management Plan (DMP) EDC specifications and Data Validation Plan ecrf setup User Acceptance Testing ecrf ready for production
Development of data management docs Define and Document the processes used to support the clinical data
Development of data management docs Data management plan (describing how the data will be managed/data Management Tasks/Responsiblities/Timelines) ecrf specifications (describing how the data will be captured in the ecrf: visits, pages, panels, items, field size, text vs numeric) Data validation plan (describing how the data will be electronically checked: automated edit checks) Data review plan (describing how the data will be manually reviewed by Data Management)
Development of data management docs Access to data (Define roles and responsibilities in agreement with sponsor)
Review of documents - Common pitfalls Comments not always clear Sponsor has not yet reached consensus on certain topics Depending on person you speak to you get different feedback Changes throughout the process
ecrf Development Design the forms to collect the data specified by the protocol (the CRF should 100% reflect the protocol sponsor approval and UAT) Keep questions, prompts and instructions clear Use multiple choice, avoid open ended questions if at all possible Maintain consistency throughout the ecrf
CRF Development common pitfall Started when draft protocol became available (because of tight timelines) The information collected in the CRF should 100% reflect the data as specified in the protocol
CRF Development common pitfall Risk of big change from draft protocol to final protocol Restart process (loss of time expensive) Error-prone
EDC Study Setup Process EDC specifications Prepare Review Approval Change control (Mid Study Changes) Data validation plan Prepare Review Approval Change control (Mid Study Changes)
EDC Study Setup Process Clinquest Services UAT environment Production environment EDC specifications Final DVP Data Entry Screens Messages/ Queries User Acceptance Testing DB release
User Acceptance Testing In UAT environment UAT Team (including CRA and sponsor) - - Review and communicate observations to Data Management - Data Management evaluates observations and communicate issues to EDC vendor - Retest until all issues are solved - Project Acceptance Document sign-off by sponsor - ecrf into production
EDC Study Conduct Process Clinquest Services Training Metrics reports + Ad hoc reports (e.g coding) Data review Query generation Monitoring query status Change control in case of database modifications
ecrf Flow Entry of data by Investigator or RN Site Source Data ecrf Datamanagement Source Data Verification (CRA) ecrf status: monitored
Data Cleaning Starts immediately (during entry) Arrange monitor visit after first data are collected in ecrf and can be checked (communicate MV dates to DM) SDV by CRA Manual review by DM (according DVP) First queries results in lessons learnt
Data Cleaning CRA and Data Manager should have same understanding on: - What CRF pages should always be completed (e.g. for early terminators: not only End of Study Form but also AE, ConMed pages)
Data Cleaning CRA and Data Manager should have same understanding on: - How should Adverse Events be recorded in the ecrf * Single diagnosis per entry (instead of different symptoms) * If single diagnosis can not be given, then a separate entry should be made of each symptoms (also to enable proper coding) * Use official terminology (no slang) * Be specific (e.g. Angina could mean Angina Pectoris or Angina Tonsillaris)
Data Cleaning CRA and Data Manager should have same understanding on : - How should medications should be recorded in the ecrf * Provide generic name (instead of Grandma s Headache Powder ) * Record only brand name in case combination drugs * Be specific (e.g. Ofloxacin instead of ear-drops) * Indication of the medication should be a medical condition or prophylaxis (e.g. not Tiazepam was given for restructuring of the house)
Data Cleaning CRA and Data Manager should have same understanding on : - How should medications should be recorded in the ecrf * Provide generic name (instead of Grandma s Headache Powder ) * Record only brand name in case combination drugs * Be specific (e.g. Ofloxacin instead of ear-drops) * Indication of the medication should be a medical condition or prophylaxis (e.g. not Tiazepam was given for restructuring of the house)
Data Cleaning CRA and Data Manager should have same understanding on : - Pay attention to the following: * For AE: if action taken is medication, a corresponding concomitant medication should be recorded * Clinical Significant lab results should also be recorded as Adverse Events * For Medication: indication (if not prophylactic) should be recorded as Adverse Event or Medical History Event
Nog aanvullen met extra voorbeelden
EDC Study Closeout Process SAE reconciliation Final review Ensure completion SDV and sign-off Lock patient records
EDC Study Closeout Process Ensure database lock/revoking access to database Ensure final data exports Data management report
Good Team Work - Involvement CRA during review ecrf specifications, ecrf completion instructions and DVP - Involvement DM during review monitoring plan - CRA also participates during UAT
Good Team Work - CRA informes DM when MV is scheduled - DM ensures that data is reviewed and queries are created before the MV - DM informs CRA when queries have been created
Good Team Work: - Discuss issues (e.g. maintain Question and Answer Log) - Important: changes in normal lab values should be communicated to DM ASAP to prevent incorrect lab queries