Research with Integrity. A Passion for Innovation. A Desire to Help.
Research with Integrity. A Passion for Innovation. A Desire to Help.
Data management is a critical component of any clinical trial. It ensures the integrity and accuracy of the data, which in turn ensures the reliability of the study’s results. Good data management practices can also help to minimize errors and improve the efficiency of reporting results. Data management begins at the planning stage of a trial, where Case Report Forms (CRFs) and procedures are developed and put into place. In many trials, a Data Management Plan is created. Data is then collected, as outlined in the study protocol, from participants at various points throughout the trial. This data is collected on CRFs and typically entered in a 21CFR Part 11 compliant Electronic Data Capture (EDC) system. Data is consistently checked for completeness and accuracy. Any errors or discrepancies are identified through queries and corrected via Data Clarification Forms (DCFs). Data analysis is then performed, usually by biostatisticians, to determine the effectiveness of the treatment being studied. Finally, the data is used to generate a report, which is used to determine whether the treatment should be approved for use. Overall, data management plays a crucial role in ensuring the validity and reliability of clinical trial results.
Data accumulated in clinical trials has limited value unless it is entered, cleaned, and analyzed properly. Our team understands what biostatisticians are looking for when they are putting together interim or final analyses. We have experience designing data base fields and the case report forms to sync with these data fields. We are able to understand the technical language that can come from biostatisticians and database developers. Our visions of what all members of a data management team see, and how they interpret things, will help ensure that the needs of all parties are met.
The design of a CRF is crucial to the success of a study, as it ensures the data collected is accurate, complete, and consistent. CRFs should be easy to understand and use, as well as be tailored to the specific study population. The form should include clear instructions for completion, and should be tested for usability before use in a study. The CRF should also be designed to minimize the potential for errors and omissions. It is also essential to consider the data analysis plan and management system when designing a CRF. Well-designed CRFs can help ensure the success of a study by providing high-quality data that is useful for research purposes.
Our clinical research experts have experience as clinical monitors, clinical research coordinators, and data managers. The familiarity with these roles can be invaluable in CRF design as each person involved in a clinical trial has different needs regarding study data.
Accurate data entry is essential for the success of clinical trials. Consistent and timely data entry ensures that the data collected is valid and reliable. Inaccurate data or delayed data entry can lead to errors in the analysis and interpretation of results, potentially invalidating the entire study. Errors in data entry can also cause delays in the trial, as they must be corrected before data can be analyzed. To ensure accurate data entry, it is important to have clear instructions and guidelines for data entry, as well as training for those responsible for entering the data.
Flyover Clinical, LLC has extensive experience in data entry. This experience includes having managed a data entry entry team, designing and validating a database, and reviewing double-data entry while moving a paper-based trial to an electronic data collection system. Also, with a familiarity of many databases, as well as a general tech savviness, reduces training time needed.
Query management is the process of identifying and resolving inconsistencies or discrepancies in the data collected during a clinical trial. It is an important aspect of data management, as it helps ensure the accuracy and completeness of the data. The goal of query management is to identify and resolve any issues as quickly as possible, to minimize delays in the trial, and ensure that the data is of high quality. The process typically involves data review by CRAs and/or Data Management. If discrepancies are identified, the persons that generated the queries work with the study team to resolve them. Timely, efficient, and effective query management is critical for the success of a clinical trial, as it helps ensure that the data collected is accurate, complete and reliable.
We have worked with queries from multiple perspectives. We know how these discrepancies are handled by research coordinator, clinical monitors, and data managers. We establish good working relationships with study coordinators at research sites, allowing us to typically resolve queries in a timely manner, without a lot of back-and-forth.
Data cleaning is the process of identifying and correcting errors and inconsistencies in the data collected during a clinical trial. The purpose of data cleaning is to bring the data to a high quality and establish integrity. Data cleaning should be performed regularly throughout the trial to minimize the time needed to make corrections later. The process is like query creation, with the CRA and data management teams working closely with the site study team to close queries within a particular timeframe.
Data freezes are often implemented at specific points during a clinical trial. During a data freeze, no further data entry or changes are made to the data, and the data is considered final. This is done to ensure that the data used for analysis is accurate and complete, and that any errors or inconsistencies have been identified and corrected.
The closeout of a clinical trial marks the end of the data collection phase. During this process, any remaining data cleaning is completed, and final data freezes are implemented. Once the data is finalized, it can be analyzed and used to draw conclusions from the study.
The Data Management Plan should have a clear plan and procedures in place for data cleaning, data freezes, and closeout, to ensure that the data collected is of high quality and can be used for accurate reporting.
Flyover Clinical, LLC can assist with data cleaning at any point in your clinical trials. Your trial may need extra help in preparation for a freeze or a trial may need to be “rescued”. We can assist in either of these situations, or anything in between.