Clinical data management (CDM) supports maintaining the raw data from clinical trials in a systematic order. Data management in clinical trials relate to the processes of gathering, recording, monitoring, analysing and reporting the clinical data. This process of clinical data management should begin at the early stages of protocol development, and end with the statistical analysis and interpretation. CDM needs to stand on a broad range of skills such as technical, scientific, project management, information technology (IT), systems engineering, and interpersonal skills to tackle, drive, and provide valued service in managing data within an anticipated span of time.

Various guidelines standardize the requirements needed for data management during clinical trials. Good Clinical Practice (GCP) guideline is one of them, was harmonised in 1996 (followed by International Conference on Harmonisation) is widely use to standardize the design and management of clinical trials. It also ensures that participant rights are protected and the data generated from the trial is gathered in a valid and replicable manner.

International Conference on Harmonization (ICH) has laid down some guidelines for clinical data management system in its sections. Here, are few sections elaborating the guideline recommendations for data management. ICH­GCP 2.10, 4.9, 5.5, 5.14 and ICH E9 3.6 and 5.8 illustrates that all the clinical research data should be recorded, handled and stored in a way that allows its accurate reporting, interpretation and verification.

ICH E6 5.1.1 determines the quality assurance and quality control systems with written standard operating procedures (SOPs) which should be implemented and maintained to ensure that research are conducted and data are generated, documented, recorded and reported in compliance with the protocol , GCP and applicable regulatory requirements. According to ICH­GCP 5.5.4, if the data is transformed during processing, it should always be possible to compare the original data and observations with the processed data. Common standards should be adopted for a number of features of research such as dictionaries of medical terms, definition and timing of main measurements and handling of protocol deviations. (ICH E9 2.1.1) Protocol amendments that necessitate a change in design of CRF, subject diaries, study worksheets, research database and other key aspects of data management processes need to be controlled as per ICH E9 2.1.2.

Data Management Plan (DMP) serves as the backbone of overall quality system of clinical data management services. It helps to proactively assess and plan for study specific data management processes. DMP plans each and every step of data management, several tasks, responsibilities, deadlines of data management unit, the creation of documents, standard operating procedure (SOP) or regulation to be followed for each activity and the degree of quality to be achieved. The preparation, review and finalization of DMP involves participation of the sponsor, lead data managers, project managers, biostatisticians, database programmers CRAs, medical monitor, laboratory directors, etc. The major elements of DMP include, protocol designing, roles and responsibilities of staff members on­site and off ­site. The data flow diagram is drawn to understand the work in a better way. The case report form (blank and annotated), data validation methods, CRF tracking and discrepancy management are discussed under DMP.