Clinical Data Management Guide

What Is Clinical Data Management? A Beginner’s Guide

Clinical data management has become an increasingly important field in the life sciences. From pharmaceutical development to managing patient records, organizations must collect, validate and maintain high-quality clinical data that meets regulatory requirements. In this blog, we define clinical data management and explore the different aspects of this essential domain.

What Is Clinical Data Management?

Clinical data management is the systematic collection, organization and validation of data obtained from clinical trials to ensure accuracy and reliability. It includes processes such as data entry, cleaning and storage in secure databases, following regulatory standards.

During clinical data management, the team will review the study protocol to understand what data needs to be captured. Then, they utilize the appropriate tools to design a system to capture, clean and store data. This system may include electronic data capture (EDC), external data transmissions and storage, data review software and programmed data listings for manual review. The clinical data management team is responsible for managing the data throughout the course of the trial until it’s ready for analysis.

What Are the Main Goals of Clinical Data Management?

The two most important goals of clinical data management include:

  1. Capturing the appropriate data based on protocol specifications
  2. Ensuring a quality database is provided to the team at the time of database lock

Without the appropriate data points and low cleaning quality, you may face prolonged timelines, missing data and incorrect data, negatively impacting your chances of a positive trial outcome. Therefore, it’s essential to thoroughly review the study protocol to determine what data the clinical team and statisticians need, ensure the appropriate tools and methods are utilized to capture the data and efficiently clean it in a timely manner before the database is locked.

What Are the Clinical Data Management Roles & Responsibilities?

Clinical data management has many essential roles to ensure a successful study. These roles include:

  • Database builders
  • Data managers
  • Medical coders
  • Site support staff

Database Builders

Database builders utilize technology to build the appropriate EDC databases that capture the clinical data. They work closely with data managers to determine the requirements for each database based on the protocol specifications.

Data Managers

Data managers are an integral part of a trial team. They are responsible for reviewing protocols, defining the specifications for the data collection tools to be used, managing all of the incoming data from the vast array of sources for data collection and cleaning the data throughout the trial for analysis preparation. They can also be heavily involved in audits and regulatory inspections.

Medical Coders

Medical coders can play a role in data management by transforming descriptions of adverse events, concomitant medications and medical history into standardized alphanumeric codes. These codes allow analysts to analyze and review the data efficiently.

Site Support Staff

Some organizations offer in-house site support to rectify any issues within the database. This allows the clinical team to receive an immediate response to their inquiries and ensure the data remains valid.

What Are Clinical Data Management Tools?

Clinical data management tools are software applications designed to collect, organize and analyze the data generated in clinical trials. They play a crucial role in maintaining data integrity, compliance with regulatory standards and efficient collaboration among researchers, contributing to the overall success of clinical research studies.

Common clinical data management tools include:

  • EDC systems
  • Data review systems
  • SAS
  • File exchange servers
  • Data visualization tools
  • Pinnacle 21/OpenCDISC Validator

EDC Systems

An EDC system is software designed to collect, manage and store data electronically in clinical trials and research studies. It replaces traditional paper-based methods, allowing researchers to enter, validate and monitor study data in a digital format.

Data Review Systems

A data review system allows researchers to monitor and evaluate clinical trial data without touching raw data. This keeps the data clean and mitigates the risk of manual errors.

SAS

A statistical analysis system (SAS) is used for tasks such as data cleaning, transformation, statistical analysis and the generation of regulatory-compliant outputs. It plays a crucial role in handling and analyzing large datasets generated during clinical research studies, helping researchers and statisticians derive meaningful insights from the collected data.

File Exchange Servers

File exchange servers enable the secure transfer and sharing of electronic files among researchers, data managers and other stakeholders involved in clinical trials. These servers facilitate the exchange of various data files, documents and information related to the study, supporting collaborative efforts and ensuring data integrity and security throughout the research process.

Data Visualization Tools

Data visualization tools transform raw data into visual formats such as charts, graphs and dashboards. This allows researchers and stakeholders to interpret and communicate data trends, patterns and insights more effectively.

Pinnacle 21/OpenCDISC Validator

A validation tool used to check compliance against CDISC outputs.

What Are the Stages of a Clinical Data Management Cycle?

The clinical data management cycle is a systematic process that involves the planning, collection, processing, validation, analysis and reporting of data generated during a clinical trial. Its purpose is to ensure the clinical data remains accurate and reliable for the entire duration of the research study.

There are three main stages:

  1. Study startup
  2. Study conduct
  3. Study lock

Stage 1: Study Startup

The study startup stage involves the initial planning and preparation for a clinical trial. During this phase, the data management team will review the protocol and provide any pertinent input, design the data collection instruments, and create the necessary documentation for regulatory submissions, such as data management plans, data review plans, etc.

Activities during the study startup set the foundation for data management processes, ensuring that the study complies with GCP and regulatory requirements and that data collection methods are well-defined and aligned with the study objectives.

Stage 2: Study Conduct

Once the study parameters are in place and you reach study initiation, it’s time for the actual execution of the clinical trial, which is known as the study conduct stage. At this time, data is systematically collected from study participants using defined protocols and data collection instruments. EDC systems help to facilitate efficient and accurate data entry.

Throughout this phase, the team will perform ongoing monitoring, quality control and adherence to the data management plan to ensure the reliability and integrity of the collected data.

Stage 3: Study Lock

During the study lock stage, data is collected and verified before the database is finalized for analysis. This is when all queries are resolved, case report forms are verified by clinical research associates and approved by the investigators, and any outstanding issues are documented.

The study team conducts a final meeting to ensure consensus on closing the study. Once everything is in order, the database is officially locked, preventing further changes. An exception to this would be to unlock a database for essential modifications that significantly impact the analysis with documented approval.

Bonus Stage: Inspections

When completing phase III trials for submission, a critical step in the clinical data management process involves the regulatory inspection that occurs upon data submission to authorities such as the:

These inspections are a rigorous examination of the trial data and processes to ensure compliance with regulatory standards and the integrity of the study.

Data managers play a pivotal role in the inspection process due to their intimate knowledge of the trial data. Their involvement encompasses providing comprehensive documentation, explaining data management procedures, and addressing any queries from regulatory agencies.

What Are the Common Challenges for Clinical Data Management?

Due to the nature of clinical data management, you can expect to face several challenges during your trial. They can include:

  • Getting sites to respond to queries in a timely manner
  • Getting the study lock to happen on time when a) external data remains outstanding from vendors, b) all case report forms have not been verified, c) investigators are lacking in approval of their case report forms in a timely fashion
  • Keeping up with the latest technologies
  • Maintaining the amount of documentation required
  • Creating and maintaining standards across therapeutic areas

The good news is that you can overcome these challenges with proper planning. For example, provide training at the start of the trial so that the sites and investigators can understand why it’s essential for them to perform their duties promptly. This helps to get their buy-in from the beginning, which leads to smoother communication later in the trial.

If you want to learn more about the newest technologies, consider attending the annual conference hosted by the Society for Clinical Data Management (SCDM). There, you will discover new innovations that can take your clinical data management to new heights.

Finally, keeping tabs on your documents is easier with an electronic trial master file (eTMF). This digital repository consolidates and organizes all of the documents related to your clinical trial, making it easier to keep track of what documents need to be signed and when. Then, you can easily bring up these documents during inspections and prove you followed the appropriate workflow.

Conclusion

Clinical data management is pivotal in clinical trials, ensuring data is processed according to regulatory standards. There are various team members and tools involved, each working together to support the goals of the study.

Firma is a specialty contact research organization (CRO) with vast experience in clinical data management. With a team of elite database builders, data managers, medical coders and site support staff, Firma has the capabilities to take your clinical data management to the next level. Contact us to start the conversation.

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