Strategies for Successful Clinical Data Management Rescue Studies

What is a rescue study?

A rescue study is a clinical trial that is being conducted by a new vendor after having previously been conducted by another vendor or in house by the sponsor. The reasons for the change may be based on issues negatively affecting timelines, costs, quality, or resources or because of changes with the study design or reporting requirements. 

When clinical data management is the reason for the rescue study, efforts are undertaken to salvage or rectify data quality and integrity issues that have arisen during the course of a clinical trial due to, for example:

  • Questionable database build quality: If the data collected in the EDC are unreliable or incomplete, the validity of the results can be compromised, limiting the ability to draw accurate conclusions.
  • Technical failures: Issues with data collection tools, electronic health records, or data management systems can result in data loss, corrupted data, poor maintenance, or major limitations.
  • Data collection and management issues: Poor data quality due to errors, inaccuracies, or inconsistencies in data collection and management can compromise database integrity.
  • Operational challenges: Issues related to site performance, participant recruitment, data monitoring, or data entry can disrupt clinical trial progress.
  • Performance: A lack of technical competency, poor planning, or inadequate communication by the vendor managing the EDC build or data cleaning scope can impair data quality.

What is the objective of clinical data management rescue studies?

Timely recognition of the existing challenges and a well-planned rescue strategy are essential to salvage the trial’s integrity and maintain the scientific validity of the research. For clinical data management, the objective of a rescue study is to ensure that the study’s results can be reliably used to support further clinical development. Rescue tasks might include rebuilding the database, cleaning the data, revalidating the data, and even re-enrolling participants, if necessary.

What are the steps to rescue clinical data management in a study?

Identify the problem

The first activity is to identify the root causes of the study data problems. Each study is unique, and a rescue plan should be tailored to fit the needs of the study.

  • Kick-off meeting with the sponsor: This meeting helps develop the scope of work and budget documents, by hearing the sponsor’s insights and concerns.
  • Request for key documents: The protocol(s), data management plan, case report forms (eCRFs, aCRFs), and other related documents and data sources should be reviewed.
  • Gap analysis: A gap analysis helps develop the transition plan, budget, and timelines, allowing discussions with the sponsor to advance to practical solutions. Based on a review of the documents and data sources, a gap analysis involves the following topics:
    • Protocol adherence: Any deviations from the protocol need to be documented and addressed appropriately.
    • Database design: Review the eCRF against the protocol, edit check specification, and any inconsistencies in the folder structure, and investigate any issues related to EDC limitations.
    • Data issues: Assess the extent and nature of data issues by reviewing data discrepancies, missing data, or inconsistencies in data collection.

Identify the solution

Once the root causes have been identified, the appropriate database transfer solutions can be discussed with the sponsor. Based on the study and sponsor needs, the solutions could include the following:

  • Building a new database with a new EDC tool

This approach is used when database design problems, along with other data integrity issues, are evident and could be both time- and cost-intensive. Creating a new database can be accomplished by programmatic remapping or manual data re-entry into a new database, a decision that is influenced by the amount of data to be transferred and extent of changes needed to the database. 

  • Transferring the database URL to the new CRO

The transfer of an existing URL to a new vendor is a more common approach than creating a new database. The new vendor assumes responsibility for the administrative tasks for maintenance, revisions, updates, and database lock. This approach may take some coordination with the original holder of the URL if there are multiple studies on the URL but could be used when problems are not limited to data cleaning and query management.

  • A multidatabase approach using database consolidation and integration with the old and new databases

Using both the old database and a newly created database would be another approach that might be used with database consolidation and integration management. This approach might be considered for a change in the middle of a larger, long-term study. Challenges would include ensuring data harmonization for data collection, analysis, and reporting.

  • Leaving the database with the original vendor and limiting the incoming CRO’s tasks to data cleaning and query management 

The least time-intensive approach is to leave the database with the original vendor and have the new vendor responsible for data cleaning and query management activities. This approach could be used when the problems are primarily with data cleaning.

Responsibilities and risks in rescue studies

Clinical data management rescue studies, although essential for retrieving compromised trial data, come with their own set of risks and challenges. Here are some common risks and key aspects of responsibilities associated with rescue studies:

  • Time restrictions: Time is of the essence in rescue studies. Delays initiating and completing the rescue process can further degrade data quality and impact study timelines.
  • Intensive use of resources: Rescue studies may require significant resources in terms of personnel, time, and budget. Allocating these resources while managing ongoing trials can strain an organization.
  • Regulatory compliance: Ensuring that all rescue study activities comply with regulatory guidelines is essential. Non-compliance can lead to regulatory issues and impact the validity of the rescue effort.
  • Documentation and reporting: Proper documentation of all actions taken during the rescue study is essential. This documentation is critical for regulatory compliance and transparency.
  • Quality control: Rigorous quality control processes should be implemented to ensure that the data are accurate and reliable after rescue efforts. This may involve independent data review and validation.
  • Validation and auditing: Independent validation and auditing of the rescue study process may be conducted to ensure the data integrity.
  • Effective communication: Maintaining transparent and effective communication among all stakeholders, including sponsors, investigators, and regulatory authorities, can be challenging but vital for a successful rescue study.
  • Study bias: There is a risk of introducing bias during a rescue study, especially when decisions about data handling and cleaning are subjective. Careful documentation and validation can mitigate this risk.
  • Impact on trial outcomes: Depending on the severity of data issues and success of the rescue effort, the final trial outcomes may still be compromised or less reliable than initially expected.
  • Costs: Due to the resource-intensive nature of rescue studies, there is a risk of exceeding the allocated budget, which can have financial implications for both the sponsor and CRO.

To mitigate these risks, careful planning, experienced personnel, adherence to regulatory guidelines, and clear documentation are essential. Organizations should also consider risk assessment and mitigation strategies specific to their rescue study scenarios to minimize the impact of these challenges on the overall integrity of the clinical trial data.

Conclusion

In summary, clinical data management rescue studies require a thorough knowledge of clinical trial processes, data quality issues, and regulatory requirements. Professionals in this field play a crucial role in salvaging and restoring the integrity of clinical trial data, ultimately ensuring that the trial results are reliable and meaningful for further analysis and decision-making. With a solid background in clinical data management and a proven track record of successfully conducting rescue studies, Veranex is a well-suited partner for rescue studies. Contact us — we are here to help.