Overview

The management of clinical data, from its collection during a trial to its extraction for analysis, has become critical in preparing a regulatory submission and obtaining approval to market a treatment. Groundbreaking on its initial publication nearly 14 years ago, and evolving with the field in each iteration since then, this latest volume includes revisions to all chapters to reflect the recent updates to ICH E6, good clinical practices, electronic data capture, and interactive response technologies. Keeping the coverage practical, the author focuses on the most critical information that impacts clinical trial conduct, providing a full end-to-end overview for clinical data managers. Features: Provides an introduction and background information for the spectrum of clinical data management tasks. Outstanding text in the industry and has been used by the Society for Clinical Data Management in creating its certification exam. Explains the high-level flow of a clinical trial from creation of the protocol through study lock. Reflects electronic data capture and interactive response technologies. Discusses using the concept of three phases in the clinical data management of a study: study startup, study conduct, and study closeout, to write procedures and train staff.

Full Product Details

Author:   Susanne Prokscha (Clinical Development Operations Excellence, California, USA)
Publisher:   Taylor & Francis Ltd
Imprint:   CRC Press
Edition:   4th edition
Weight:   0.453kg
ISBN:  

9781032495583

ISBN 10:   1032495588
Pages:   250
Publication Date:   03 July 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Preface Acknowledgements Common Acronyms Introduction to Clinical Trials Testing in Humans Clinical Trial Protocols Clinical Trial Process The Importance of Clinical Data Management Regulations, Guidance, and ICH E6 (GCP) Part I: Study Startup Chapter 1: The Data Management Plan Purpose of Data Management Plans Contents of the DMP Initiating the DMP Approving the DMP Revising the DMP Using DMPs with CROs The Value of Data Management Plans Data Quality and DMPs SOPs for DMPs Chapter 2: CRF Design Considerations Primary Goals of CRF Design Collecting Required Data: Visits, Forms, & Fields Collecting Analyzable Data Protocol Compliance CRFs Linked to Non-CRF Data Reuse and Refine CRF Modules Data Quality through CRF Design SOPs on CRF Design Chapter 3: Selecting Edit Checks Identifying Possible Edit Checks Focus on Critical Variables Data Validation/Edit Check Specifications Updating Data Validation Specifications Data Quality through Data Validation SOPs for Data Validation Checks Chapter 4: EDC Study Build and Release eCRF Build Data Validation/Edit Check Programming EDC Study Testing Release to Production Change Control Data Quality for eCRFs and Edit Checks SOPs on EDC Build Chapter 5: Planning for Blinded Studies Background on Blinding Maintaining the Blind Accidental Unblinding Unblinded Study Team Members Blinding Impacts Data Quality SOPs and Study Plans for Blinding Chapter 6: Patient Reported Outcomes Background to Patient Reported Outcomes Licensing PRO Questionnaires Considerations for Electronic Collection Consideration for Paper Instruments Protocol Compliance Budgeting Time and Money Quality Assurance for ePRO SOPs and Study Plans for ePRO Part II: Study Conduct Chapter 7: Overseeing eCRF Data Entry Tracking Participants Enrolled Forms Entered vs Forms Expected Tracking Investigator Signatures Monitoring Data Entry Benefits Data Quality SOPs and Plans for Overseeing eCRF Data Collection Chapter 8: Managing Queries System Queries Manual Queries Tracking Open Queries Quality Control for Queries Using Queries to Improve Quality SOPs and Plans for Managing Queries Chapter 9: Collecting Adverse Event Data Collecting AEs and SAEs Adverse Event Forms Storing and Cleaning AE Data Coding Adverse Event Terms Reconciling Serious Adverse Events Coding and Reconciliation Approvals Data Quality for AEs SOPs and Study Plans for AE Data Chapter 10: Managing Lab Data Data Management for Lab Data Lab Test Names Storing Units Lab Reference Ranges Laboratory Identification Central Labs Using Specialty Labs Data Quality for Lab Results SOPs and Study Plans for Processing Lab Data Chapter 11: Receiving Non-CRF Data Receiving Electronic Files from a Vendor Cleaning Non-CRF Data Managing Blinded Data Data Quality for External Data SOPs and Study Plans for Non-CRF Data Chapter 12: Data Review Edit Checks vs Data Review Data Review Plan Performing Data Review Planning for Manual Queries Data Quality and Manual Data Reviews SOPs and Study Plans for Data Review Chapter 13: Risk-Based Quality Management Background A Structure for Risk-Based Quality Management Centralized Monitoring Working with Clinical Operations RBQM is Quality Assurance SOPs and Study Plans for RBQM Chapter 14: Managing EDC Changes Change Control for Studies eCRF Changes Edit Check Changes Other Study Changes Testing and Approval Impact on Investigator Signatures Changes Associated with a Protocol Amendment Maintaining Data Quality during EDC Study Changes SOPs for EDC Changes Part III: Study Lock Chapter 15: Study Lock Core Requirements for Study Lock Final Study Lock Interim Study Lock Data Extract Plans or Specifications Soft Lock Time to Study Database Lock Final Data Quality SOPs and Study Plans for Study Locks Chapter 16: After Study Lock Post-Lock Activities Unlocking EDC Studies Data Quality and TMF Quality SOPs and Sutdy Plans for Post-Lock and Unlock Part IV: Necessary Infrastructure Chapter 17: SOPs for CDM What Is an SOP? SOPs for Data Management Creating SOPs Complying with SOPs SOP on SOPs Quality Assurance through SOP Revisions Chapter 18: CDM and the TMF TMF Reference Model Reviewing the Study Reference Model Submitting to the TMF TMF QC Supporting Documents, Email, and NTFs Living with the TMF Chapter 19: Training Minimum Required Training Training Matrices How to Train Training Records Experience and Education Allotting Time for Training SOPs on Training Chapter 20: User Management Account Management Access Control through Roles Taking Security Seriously SOPs and Guidelines for Accounts Chapter 21: Developing and Using Standards The Goal and Purpose of Standards\ Industry Standards Where to Start Standards Team Governance Using Standards SOPs for Standards Chapter 22: Working with Service Providers Data Management CROs The CRO Myth Qualifying CROs Defining Responsibilities Oversight Metrics Oversight During the Trial Resourcing EDC Vendors as CROs Functional Service Providers Benefiting from CROs SOPs for working with CROs Part V: Using Computerized Systems Chapter 23: Data Integrity What is Data Integrity? Integrity in the Data Lifecycle Demonstrating Integrity in Transfers Applying Risk Assessments Chapter 24: Data in EDC Systems Control of Data: Hosting Data Entry by the Sponsor or CRO Need for Data Repositories Chapter 25: Choosing Vendor Systems Defining Business Needs Initial Data Gathering Extended Demos and Pilots Additional Considerations What is Missing? Qualifying a Vendor Preparing for Implementation Chapter 26: Implementation Planning Overview and Related Plans Essential Preparation Validation Integration and Extensions Migration of Legacy Data Benefiting from Pilots Assessing SOPs and Other Documents Preparation for Production Successful Implementation Chapter 27: System Validation What Is System Validation? Systems that Require Validation Validation for Hosted Systems Validation Plan Validation Testing Validation Report Change Control Requirements and Benefits Chapter 28: Migrating and Archiving Data Regulatory Expectations When to Migrate EDC Migrations Complex Migrations Migration by Re-Entry Audit Trails in Migrations Archiving and Decommissioning Migration and Archive Plans Data Integrity for Migrations and Archives Chapter 29: EDC Study Rebuilds Circumstances Leading to Rebuilds eCRF and Edit Check Rebuild Moving Data Investigator Signatures Integrated Systems Site Impact Documentation Appendix A: Data Management Plan Template Appendix B: Data Extract Plan Template Appendix C: System Implementation Outline Index

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Author Information

Susanne Prokscha has been involved in clinical data management (CDM) processes and technologies since the mid-1980's. She has worked both as a consultant and directly for companies large and small, gaining experience with a wide range of studies and a variety of CDM systems. Since 2007, Susanne has been focusing on standard operating procedure (SOP) development, document management, and training plans for CDM and for other functions in clinical research and development.

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