Data Management
Our mission is to deliver regulatorily compliant, innovative, and efficient data management to contribute to high quality research.
Data management refers to the processes involved in planning, collecting, organising, processing, storing, and maintaining data within research trials for the duration of the study.
Good data management practices and processes are essential when conducting research. They ensure high-quality research output and data integrity, i.e. ensuring that data is accurate, consistent, and complete. This includes effectively managing the data itself, along with associated data systems or databases, and relevant data-related study documentation.
Why data management is important to research
Data management begins at study set-up, when data management is planned. During a live study period, research teams handle the day-to-day management of data and data collection. When a study ends, data is analysed, preserved, and shared for use and publication.
The data lifecycle
Research data management can be seen in terms of a data lifecycle, which illustrates the data flow throughout the study. Each stage of the study requires different data-related activities. The role of a Data Manager is to ensure that these activities and the relevant processes are in place, allowing the research data to be managed effectively.
Study setup
Planning: Planning takes place during the trial set-up stage to develop the data management for the opening of the study. Data management tasks at this stage include:
- Writing the data management plan
- Collaborating with key contacts such as the Chief Investigator, Trial Manager, Trial Statistician and Information System Developer to develop the database system specification and data capture requirements (including any reports and study management that will be required) to ensure the study endpoints are met
- Developing the metadata (this contains data about data: a document containing all variables and validations used to collect the data and inform the database build) and Case Report Forms (CRFs)
- Developing testing scripts and testing the database
- Providing input into the protocol (data management section)
- Developing training documentation and videos
- Obtaining all required peer-reviews and sign offs for data management documentation
Open to recruitment
Data Collection, Data Processing: After the study opens to recruitment, data collection takes place and the data is processed and cleaned by the Data Manager to ensure that it is complete, accurate and able to be used. Tasks here include:
- Data querying
- Processing change requests/form amendments/new forms and testing
- Producing project team reports (e.g. recruitment, withdrawals, follow up)
- Data cleaning
- Carrying out quality control checks of data
- Carrying out audit trail checks
- Data monitoring (toxicities, follow ups, withdrawals)
- Completing central monitoring and any site monitoring as required
- Ensuring essential study documents are up to date and regularly reviewed
- Answering day to day site queries
- Supporting on-site or remote site monitoring activities
- Supporting data-sharing requests
- Undertaking research activities to support the study such as abstracts/poster submissions to conferences
Study closure
Analysis, Preservation, Sharing, Re-use: At the end of the study, the data is prepared for analysis and the research written up for publication. Data is required to be preserved via archiving for future use and to validate the research findings. Where required, data should be shared and be accessible for future research. Data management actions for closure include:
- Ensuring all data queries are closed
- Working closely with sites and the Trial Statistician to clean data and prepare a final data export
- Locking the study database
- Working with Trial Manager to assist in trial close out tasks, including ensuring sites are closed appropriately
- Returning data to sites
Contributing to the final report to funders and papers assigned on the publication policy
- Guiding principles/methodology
- Unique expertise in the data management team
- Data management publications
- And a one sentence “mission statement” to go at the beginning
Standard Operating Procedures
Across all of our trials and studies we use the same Standard Operating Procedures (SOPs) and Policies. These ensure that the work we do is conducted in compliance with regulation. Our policies are:
- Data Management Policy
- General Data Protection Regulation: CTR Policy
- Case Report Design
- Metadata and System Specification
- User Acceptance Testing
- Data Management and Data Management Plan
- Withdrawal of Participants
- Returning Data to trial sites
Publications
All Data Managers are employed as researchers and therefore contribute to publications from their trials and studies.
Data Managers also look to get involved in their own methodological research in order to increase the evidence base for making our trials more efficient in the way that they are run. This is often completed via studies within a trial (SWATs). A SWAT is a self-contained research study that has been embedded within a host trial with the aim of evaluating or exploring alternative ways of delivering or organising a particular trial process.
A SWAT seeks to resolve important uncertainties about the processes used in trials. It can be evaluated in a single trial, but is well-suited for running across more than one host trial, either at the same time or sequentially. It will provide data to inform the design and conduct of future trials but might also provide data to inform decisions about the ongoing host trial. All published SWAT protocols are published on the Northern Ireland repository.
Example SWATs from CTR are:
- Modes of data collection for subjective outcomes at follow-up: comparing a choice and a failure-based approach
- Impact of recruitment plan on participant recruitment
- SMS prompts to improve compliance with study procedures
Team structure
The data management team is led by Nigel Kirby and currently consists of 24 members, including 4 Senior Data Managers, who are divisionally aligned:
- Brain Health and Mental Wellbeing – Mia Sydenham
- Cancer – Ceri Frayne
- Infections, Inflammation and Immunity (i3) – Debbie Harris
- Population Health – Helen Stanton
Each new study is assigned a Data Manager and, where appropriate, a Senior Data Manager.
