Clinical data management Best practices

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Data Management overview

Clinical Data Management Best Practices

Protocol CRF Design Database Design/ Building Edit checks/Specifications. Data Entry Data Validation/ Coding SAE Reconciliation Database Lock/ Transfer Statistical Analysis

Data Management Components
Data Acquisition Data Privacy Data storage Data Entry Data Archival Quality in Data Management Data Security and Confidentiality

Data Management Objectives
Primary:- Ensure Data Integrity Secondary : Accelerate timelines from data collection to data analysis and publication. Work closely with researchers in every stage of the project life cycle

Data Acquisition
Design the forms to collect the data specified by the protocol. Keep questions, prompts and instructions clear and concise. Use multiple choice avoid open ended questions if at all possible. Maintain consistency throughout instruments. Make the forms available for review at the clinical site prior to approval.

Data Privacy
Educate and train all project personnel. Minimize identifiers in data collection. Protect non-entered data which could impact client confidentiality. Ensure privacy during data transfer. Design policies and regulations. Implement contract contingencies when utilizing external services. Maintain proper physical and electronic security measures. Signed the confidentiality agreement from all project personnel.

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Data Storage
Store all original data collected in secured areas such as rooms with controlled access. Document the procedures for granting access to database servers establishing system controls and assigning passwords. Store electronic data in such a way that backups can be made easily and frequently. IT disaster recovery plan.

Data Entry
Independent Double Entry Double entry with blind verification. Double entry with interactive verification. Single entry with manual review.

Data Archival
Lock the database to prevent data modification. Create database design documentation. Preserve raw data.

Quality in Data Management
Betterment in quality leads to increases in productivity rate of innovation and profitability.

ICH- GCP: Section: 5.1.3

Data Security and Confidentiality
Aspects of Security Physical Security Data Security Communication Security Software Security. Data protection act-1998/ ISO-IEC-17799, BS-7799 part 2: 1999 FDA 21 CFR part 11: Final rule-Federal Register Vol-62, No-54 13429 March 1997.

Scope of Clinical Data Management
System Study Compound Corporate

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System Level
Plat form Security Availability Configuration Dictionaries Work Flows Acquisition/ Integration Secure regulated environment

Study Level
CRF Design Database Design Study Configuration Security Data Procession[ Entry/Validation] Data Tracking Data Reporting Data Audits Data Lock Complete Accurate, Auditable Data

Compound Level
Data Integration Data Reporting Statistical Analysis

Corporate Level
Tracking Metrics Timelines Resources

Business objective planning

Data Management Set-up
Data Validation Guidelines SAE Reconciliation Guidelines Creation and Implementation of a Quality Control plan Coding of Clinical Data Handling Data Transfer Designing a Case Report Form Handling Non-CRF Data Data Handling Report Building a Project Database Account management, Security and Access Data Entry/Tracking Guidelines

Data Validation
Automated and manual procedures to detect missing entries, illogical data or data that conflict with the protocol requirements. To ensure Data accuracy and Completeness.

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Discrepancy Management
Is the process of identifying and managing potential problems with data collected during a study. Discrepancy is a variance between an actual response and the expected response as defined in validation procedures. Discrepancy doesn’t necessarily indicate an error with the data only that the data doesn’t meet expectations. Discrepancies are resolved according to the protocol and Guidelines. Batch Validation: A process to programmatically run all associated procedures against all accessible data for a specified study. Data Clarification Form: Form used to clarify discrepancies identified in the clinical data reported on CRFs and to document modifications.

Data Validation Guidelines
Global Ruling Edit specifications Data/DCF flow

SAE Reconciliation Guidelines
Reconciliation is the process where data management ensures that the SAEs that are recorded in the CDMS match those recorded in the Drug Safety database [ Pharmacovigilence Database]

Clinical Data ManagementOutsourcing to India
Business Need:A Detailed Data Management Plan Preparation of database in a desired software Comprehensive electronic validation and consistency checks Data entry including double entry Query generation, handling, editing and tracking. Database lock 100% quality control of the efficacy parameters and safety data 21 CFR part 11 compliant

Data Management setup Cost
Cost of manpower Office maintenance Data Management software Thesaurus management system Application Server Media charges Dictionary Statistical Software Servers Operating System Implementation & Training Expenses Personal computers Cost of Hardware, Software Telephone charges

Challenges and Opportunities
Perceptions versus ground realities in India Lack of Intellectual property protection Ethical Standards- GCP compliance and Law Acceptance of Indian data for submission to the FDA and committee for proprietary medicinal products. Regulatory reforms to facilitate global trials in India Indian GCP guidelines and its regulatory status. Investigator capability status Setting up in-house dedicated clinical operations. Back office services support e-CRF and Database development Data Management Statistical analysis and SAS programming

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Improving Clinical Trials by Implementing Information Technology
Core functions-Target for Improvement:Protocol design and study start up Patient and investigator recruitment Clinical trial management Clinical data management Data Analysis Clinical supplies Regulatory and Safety Electronic Data Capture

Conclusion
India- Emerging Outsourcing Model Preferred full service provider Functional service provider IT superpower and Clinical Trial hub Quality and fast response-buzzword Meeting global stringent regulatory standards Proactive risk management and innovative in technology

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