Clinical Data Management (CDM) and Clinical Data Services

What is clinical data management?

Clinical data management (CDM) is the process of collecting, handling, storing, and processing data from clinical trials in accordance with trial protocol and applicable regulatory requirements. To carry out these activities effectively and accurately, a CDM team, usually led by a clinical data manager, performs various duties, from organizing data collection methodologies to developing the clinical database(s) for managing the collected information. The primary purpose of CDM is to ensure patient safety and the quality and reliability of clinical trial data in order to meet FDA regulations (in the US, or applicable regulations outside of the US).

What is a CDMS?

CDMS is the abbreviation for clinical data management system, a software tool designed to streamline data management workflows for clinical researchers and trial sponsors. A CDMS may integrate directly with data entry sources such as electronic data capture (EDC) and electronic case report forms (eCRFs), as well as other eClinical solutions like clinical trial management systems (CTMS) and electronic quality management systems (eQMS).


The Clinical Data Interchange Standards Consortium, or CDISC, is a global non-profit headquartered in the US that aims to enhance trial quality and clarity by establishing high-quality clinical research data management standards. Their Clinical Data Acquisition Standards Harmonization (CDASH) model for data collection seeks to optimize the traceability and transparency of study data for regulatory bodies and trial data reviewers by facilitating data organization in the Study Data Tabulation Model (SDTM) format.[1]

Why is CDM important in clinical research?

Data management plays an important role throughout the entire life cycle of a clinical trial. In addition to being necessary for regulatory compliance and submissions or reviews, properly managed data can help avoid costly delays and setbacks during trials. Further, efficient data management practices support faster and more informed decision-making, which has positive impacts on patient safety, process efficiency, and overall study timelines.

CDM usually involves leveraging software tools (primarily CDMS) for collecting, tracking, storing, validating, and analyzing data. Secure data storage, ethical and responsible handling of personal health information, upholding of patient confidentiality, and strong documentation trails are also essential considerations within the realm of clinical data management.

Steps involved in clinical data management

CDM typically follows a structured workflow divided into several phases:

  1. Planning & setup (study start-up): Creating the study database, designing the data management plan (DMP), creating/updating and reviewing standard operating procedures (SOPs) for all data handling steps.
  2. Data collection: Entering study data (either actively or passively via technologies such as wearable devices), and continually verifying/validating data (manually or through automated edit checks, or usually a combination of both).
  3. Documenting and resolving queries: Data is consistently checked for errors; any errors identified are registered as queries which are marked for resolution by the appropriate person. This could involve the simple correction of typos, or might require in-person site visits by the trial monitor to identify the root cause of systematic issues or critical errors.
  4. Database freezing/locking: A 2-step process that begins after all study data has been collected. The database is locked after it has been thoroughly cleaned and has undergone a quality assurance review, and data can then be analyzed, usually by dedicated statisticians who form part of the CDM team.
  5. Reporting: Final study results generated through the statistical analysis of the finalized clinical database are communicated to the trial sponsor.
  6. Study close-out: Includes study termination and archiving of the study data, in accordance with applicable regulations.

During each stage of the clinical data management workflow, it is important to maintain clean data as well as properly document all data handling activities, in case this information is needed for regulatory submission or review/audit. The data management plan (DMP) should include SOPs outlining ethical and responsible data handling practices for all stages of the data management workflow.

Outsourcing clinical data management services to external providers

In some cases, clinical trial sponsors might decide to outsource their clinical data management operations. By taking this approach, timelines can be cut down by delegating the data management tasks to specialists with extensive experience in clinical data management. These service providers will be proficient in aspects of compliance and patient data privacy/confidentiality (such as HIPAA, GCP, etc.), and will have established workflows to streamline data processing in a secure and professional way. Full-service external providers will bring together various components such as statistics, programming, and medical writing together into one package deal that can be customized to fit the sponsor’s/trial’s specific needs.

Particularly for sponsors of single trials, or those who do not have an interest in establishing internal data management teams and processes, outsourcing to clinical data management companies may be an attractive option. Clinical data management suppliers should be able to offer faster study completion times with reduced project overhead expenses that would be associated with aspects such as software licensing fees, staff training, and wages if internal employees were used instead.

However, in other cases it may be better to develop strong internal protocols and capabilities, especially for sponsors planning to conduct multiple trials into the future. In such cases, having an internal CDM team may help streamline overall workflows and be more cost-efficient in the long run. Pharmaceutical companies who choose to go the internal route may still want to use third-party data management software to enhance process efficiency and set their team up with powerful electronic tools for optimizing data collection, validation, and sharing. In this way, sponsors will be better equipped to control the flow of information within their organization and to thoroughly monitor data management operations.

Top clinical data management service providers

Many clinical data service providers offer these services as part of comprehensive, all-in-one solutions for trial sponsors, but these solutions can usually be customized or used in a modular fashion, contracting only the services needed. Others offer services specifically related to clinical data management. It is important to do some research to ensure that a provider fulfills exactly the services you are looking to contract. Some of the most trusted clinical data management companies in 2023 include:

*Note that these are listed in no particular order