All clinical trials and studies should have a Data Management Plan (DMP), to ensure compliance with good data management practices. DMP is a written document that describes the plans for the collection and management of data throughout the lifecycle of a clinical trial. For effective data management, planning must begin at the time of trial design. It should consider the collection and management of data during the trial, data sharing and archiving at trial closure. It is the responsibility of the Data Manager to ensure that all tasks and procedures detailed in this plan are carried out. It is essential that a DMP for a trial is ready before data collection starts. This will ensure that the data is in the correct format, organized and annotated appropriately. A well-designed DMP will provide a road map on how to handle the data, establish processes to handle unforeseeable conditions and assess potential risks. The ideal end result is to provide a database that is accurate, reliable, secure, and ready for analysis.
As there are various stakeholders and staff members involved in data handling, throughout the trial, it is imperative that all parties involved are qualified (in terms of experience and training) to perform their roles and responsibilities within the trial. The purpose of developing a DMP is to document the processes and procedures to facilitate consistent, efficient and reliable data management practices, for a clinical trial. The key goal of this document is to communicate to each stakeholder the required information to create and maintain a high-quality database that is ready for analysis. In addition to the database specification, DMP should also document CRF design and development.
Though the DMP is developed during the set-up phase of a trial, it should be considered a working document, to capture all changes that are made, which might impact data management.
The following are recommended for developing a DMP:
- A draft of DMP must be available before the enrolment of the first trial participant.
- The DMP must be written in compliance with applicable regulatory requirements, oversight committees and relevant Standard Operating Procedures (SOP).
- The DMP must clearly identify the roles and responsibilities of the data management group/team.
- Data management processes must be clearly defined from trial initiation to database lock.
- Data archiving and data sharing should also be documented in the DMP
The minimal set of components and elements that should be included in a DMP or other documents associated with data management of a trial are specified by ICPSR and can be accessed here. However, it is imperative that the DMP is developed as per the regulatory requirements and the type of trial to be conducted.
It is considered best practice to develop the DMP in collaboration with all stakeholders involved in the trial, to ensure compliance. Institutes and agencies involved in clinical research might consider developing DMP templates, which are customised as per the requirements of the trial. Prior to the commencement of the trial or the study, the DMP should be signed and approved by all stakeholders or responsible parties.
This document is meant to serve as a guidance or a suggestive template to prepare a DMP.
Following is a list of recommended SOPs:
- Case Record Form Design and Development
- Database Design and User Acceptance Testing
- Data Management (including roles and responsibilities)
- Data Entry
- Internal Data Handling
- External Data Handling
- Data Cleaning
- Serious Adverse Events Data Reconciliation
- Quality Control
- Database Lock and Unlock
References and Further Reading
- Good Clinical Practices for Clinical Research in India, Central Drugs Standard Control Organization, 2017, available online.
- Good Clinical Data Management Practices, published by Society for Clinical Data Management, 2013.
- International Conference on Harmonization, Guideline for Good Clinical Practice, E6(R2), 1996, available online.
- Clinical Development Services Agency SOP for Creation and Maintenance of Data Management Plans, 2018, version 1.1.
- Clinical Data Interchange Standards Consortium (CDISC): CDISC Foundational Standards are a complete suite of standards that support medical research of any type, from protocol through analysis and reporting of results. CDISC also focuses on core principles for defining data standards and models for study data tabulation. It is recommended that the CDISC website and published standards and models are referred to while developing a Data Management Plan for a trial.
- General Principles of Software Validation; Final Guidance for Industry and FDA Staff, U.S. Department of Health and Human Services, Food and Drug Administration, version 1.1, dated 11th January 2002, available online (last accessed on 06.03.2019).
- National Guidelines for Data Quality in Surveys, Indian Council ofÂ Medical Research – National Institute of Medical Statistics, dated July 2021, available online (last accessed on 09.03.2022).
- National Data Quality Forum (NDQF) – has a Data Quality Library and a Knowledge Centre â€“ researchers utilising data in their research work can access useful articles and book chapters.