Data Management & Their Plans

data-integrityClinical Data Management (CDM) encompasses the entry, verification, validation, and quality control of data gathered during the conduct of a clinical trial.

The clinical data manager plays a key role in the setup and conduct of a clinical trial. The data collected during a clinical trial forms the basis of subsequent safety and efficacy analysis which in turn drive decision making on product development in the pharmaceutical industry.

Society for Clinical Data Management (SCDM) is professional membership-based  organization founded to advance the discipline, by providing: networking, training, and a certification exam based on their Good Clinical Data Management Practices (GCDMP) handbook, that was developed to provide guidance on accepted best practices and minimum standards for the many areas of CDM not covered by existing regulations and guidance documents.

The Association for Clinical Data Management (ACDM) is also a professional organization, whose website offers a diverse, valuable resource for all levels of professional people managing clinical data. They aim to promote best practices, share knowledge and assist with the professional development of our growing membership.


Clinical Data Management is Key in Supporting Regulation

An effective training program plays a key role in ensuring regulatory compliance, performance effectiveness, and job satisfaction of clinical data management (CDM) employees. There are a number of compelling reasons for developing and implementing effective training programs. Good Clinical Practices (GCP) and other regulatory guidance documents state that all personnel involved in clinical trials must be qualified and properly trained to perform their respective tasks.


Project Management 

Data managers should know basic principles of project management, regardless of the extent of project management activities that are assigned to CDM. Effective application of project management principles results in improved quality and timeliness of CDM deliverables, as well as increased efficiency of CDM functions.

Vendor Mangement: Vendors provide services that are critical to the successful outcome of a clinical study, however the as ICH E6  states “Ultimate responsibility for the quality and integrity of the trial data always resides with the sponsor.” including activities that are outsourced. If a sponsor is willing to give control of some study activities to a Contract Research Organization (CRO), specially those having any impact on final data quality, the sponsor should take measures to ensure the vendor is delivering products or services of acceptable and repeatable quality.


The Data Management Plan

The optimal end result for a clinical data manager is to provide a study database that is accurate, secure, reliable, and ready for analysis. The Data Management Plan (DMP) provides a consistent approach to the process and guidelines for conducting data management activities. Including the design of Case Report Forms (CRFs) as defined by ICH E6 guidelines: “A printed, optical, or electronic document designed to record all of the protocol-required information to be reported to the sponsor on each trial subject.” Also a Database Validation Plan per Code of Federal Regulations Title 21, Volume 1, Part 11 that mandates that procedures and controls be in place to ensure appropriate control of and access to documentation as well as revision and change control procedures to maintain an audit trail of modifications to documentation. The DMP is an auditable document asked by regulatory inspectors. During audits, inspectors will try to ascertain the degree to which the project team adheres to the DMP processes.


CDM and Their Metrics

The term “metric” simply refers to a measurement. In clinical data management, metrics can quantitatively and qualitatively assess whether or not a process or individual or group performance is efficient and effective, as well as indicate whether the factor being measured has or will have an expected level of quality. Metrics can be used at various intervals throughout a study to ascertain if processes are working as planned. When a process has  been completed, well-designed metrics can help indicate if goals were achieved with the expected level of quality.