Clinical Data Management (CDM) is the process of putting together, handling, collecting and analysis of clinical data, which is done in accordance with regulatory requirements. The field of Clinical Data Management was established due to demands from the pharmaceutical industry and regulatory authorities as a way to ensure that quality-assurance standards have been met while collecting data during a clinical trial.
The process of CDM begins before the study protocol has even been finalised. A Data Management Plan (DMP) is developed as a guide that includes a detailed description of the clinical trial’s CDM processes.
Key Roles Involved in CDM
Data Manager: A person who oversees the entire CDM process. They ensure that the research staff collects, manages and prepares the data accurately and securely. They work with different types of clinical data including administrative data, Case Report Forms (CRFs), electronic health records, laboratory data, patent and disease registries and safety data. The Data Manager is also expected to apply quality control checks at each stage of data handling, resolve any inconsistent data and code adverse events correctly using Common Terminology Criteria for Adverse Effects (CTCAE).
Database Programmer/Designer: Somebody who creates the clinical trial database, designs data entry screens, enables data validation and performs edit checks using dummy/test data.
Clinical/Medical Coder: Responsible for transforming reports into universal medical alphanumeric codes, especially cases of serious adverse events and the medical history of participants.
Clinical Data Coordinator: In charge of managing and organising data that has been collected from various departments and clinical trial programs. They ensure that the database is updated with accurate information, identify any errors and maintain records of transactions.
Quality Control Associate: Checks the accuracy of the data entries and performs data audits.
Data Entry Associate: Responsible for collecting information about the participants, tracking the receipts on the Case Report Form (CRF) and entering the data into the database.
Research Nurse: A nurse who works with participants during clinical trials while recording and managing data. Provides accurate and complete source documentation while implementing a Quality Control (QC) plan.
All research staff should:
- Ensure that all data is documented with accuracy, completeness and consistency.
- Ensure that the data collected is verifiable and acceptable for sponsor submissions and publications.
- Review and correct any data discrepancies.
Data Management Steps
Plan: The data manager prepares the database and the overall data management plan.
Collect: The CDM team collects data throughout the course of the trial.
Assure: The Data Manager decides if the data plan and software meet the requirements.
Identify: The CDM team identifies any issues or risks.
Preserve: The Data Manager preserves the data already collected.
Integrate: The Data Manager oversees the data and ensures that it’s all consistent.
Analyse: Data trends and outcomes are mapped and analysed.
Lock: The database is locked to preserve its integrity.
Models for Data Management in Clinical Trials
Clinical Data Management has various areas of responsibility including:
Clinical Systems: The software, technology or database used.
Data Management: Data collection, coding and standardization.
Data Review and Analytics: Quality management, auditing, and analysis of the collected data.
Data Standards: Checking that the data complies with the regulatory requirements.
Innovation: Using the newest technologies and databases in the field.
Data Management Workflow
Case Report Form (CRF): The CRF design forms the basis of initial data collection.
Database Design: The database should work well and have enough space for all the data collected during the clinical trial.
Data Mapping: Integrates data from different forms/formats so researchers can easily report it.
Serious Adverse Events (SAE) Reconciliation: Data managers should regularly review and correct severe adverse events and potential risks.
Database Locking: Once the trial is completed, the Data Manager should lock the database so that the data can’t be edited or changed.
Clinical Data Management Plans
A Clinical Data Management Plan should outline all the data management work needed in a clinical trial, including the timeline, any milestones and deliverables. The plan should be comprehensive and includes a template which provides trial staff with a clear idea of how to develop a Data Management Plan which is specific and relevant to their study.
Clinical Trial Data Validation Plan
Involves resolving database inconsistencies by double-checking the data for accuracy and completeness. Once the data collection has been completed, the results can be organised into tables, lists and graphs and are then integrated into a higher-level document (Investigator’s Brochure or Clinical Case Study Reports). The Data Manager archives the database and locks it to preserve its integrity. Some clinical studies need more frequent data validation.
What is a Clinical Trial Management System (CTMS)?
A Clinical Trial Management System (CTMS) is a project management software that is specially designed for clinical research and clinical data management. It enables the planning, reporting and tracking of all steps of a clinical trial with an end goal that ensures that trials are efficient, compliant and successful. A CTMS allows companies to build trust with regulatory agencies, as accurate study results and data collection lend credence to research clinical trial data.
All software and databases should be set up before the clinical trial begins as software changes during the trial can be expensive and can have a negative effect on the trial data’s validity.
Case Report Form (CRF)
A Case Report Form is a data-reporting document that is used in a clinical trial and enables efficient and complete data collection, processing, analysis and reporting. It is the main tool that investigators use to collect information from clinical trial participants. CRFs are designed in compliance with the study protocol in which all participants' details are recorded. There should be one CRF book completed for each participant.
CRFs allow for data to be collected with users in mind and in accordance with regulatory requirements. The data questions should be clear and concise and duplication should be avoided. Its paper and electronic interface allows for an exchange of data across projects and companies through standardisation.
Quality Control (QC)
- An ongoing review of participant data which includes checking your own work and others.
- Verify data collected and that it has been correctly entered into the databases.
- Follows regulations and guidelines.
- Should be applied to each stage of data collection.
- Ensures that all the data collected is complete and accurate.
Quality Assurance (QA)
- A planned, systematic check carried out at an organisational level.
- Checks that the data generated is accurate.
- Ensures that the trial is performed in accordance with the plan.
- Identifies problems and trends.
- Ensures the staff is working in accordance with guidelines and regulations.
Additional Clinical Trial Data Management Activities
- Central laboratory data.
- Data archiving.
- Data entry and validation.
- Data extraction.
- Data queries and analysis.
- Data storage and privacy.
- Database design, build and testing.
- Discrepancy management.
- Medical data coding and processing.
- Severe Adverse Events (SAE) reconciliation.
- Study metrics and tracking.
- Quality control and assurance.
- Validation checklist.
Regulations, Standards and Guidelines for CDM
There are different standards, regulations and guidelines which provide guidance to the Clinical Data Management team. The Clinical Data Interchange Standards Consortium (CDISC) is an international organisation which ensures that clinical trials are following international regulations, state laws and standard operating procedures (SOPs).
If the trial follows all the appropriate regulations, it shows that the trial has been conducted with integrity and that the data collected can be trusted.