Data Management

Data management is the process of collecting the raw data, entering them in computers for analysis, analyzing them, writing reports, formatting them for submission to regulatory agencies, and proper long-term storage.

[Page 128]Most research teams use standardized and newly created tools to collect, process, analyze, and audit data. Tools vary in format from visual analog scales to open-ended questionnaires. Examples of tools for participants to use to self-report data include diaries, calendars, logs, and surveys. The case report form is the basic tool of data abstraction. Many reports use a Web-based format; others are paper based. The National Cancer Institute (NCI) is constructing an informatics system that will reduce the extensive paperwork often associated with clinical trials. For example, the Common Toxicity Criteria (CTC), a Web-based, interactive application, uses standardized language to identify and grade adverse events in cancer clinical trials. Forms are also available for rapid reporting of adverse events, electronically or by telephone, to alert researchers to potential safety issues. The Adverse Event Expedited Reporting System (AdEERS) is a Web-based program that enables researchers using NCI-sponsored investigational agents to expedite the reporting of serious and unexpected adverse events directly to the NCI and the FDA.

A written data management plan (DMP) is a critical element in conducting a successful clinical study or trial. The DMP is usually very general during the protocol development stage, but immediately before study initiation it should become very detailed. A typical DMP provides detailed descriptions of how the following areas will be addressed during the clinical trial:

• CRF processing: How will completed CRFs be tracked, filed, and handled in the data entry area?
• Data entry: How will staff be trained? Will data be double-entered? How will differences in the data be resolved?
• Validation and query generation: Who decides how data will be verified? What documentation is needed? How will programming be tested?
• Query management: How will queries be tracked? How will queries be resolved? How will the main database be updated?
• Coding: Which questions have open-ended text that needs to be grouped for table presentations? Which questions need to be coded with standard medical terminology, and what standard medical terminology should be used?
• Filing: Where will CRFs be filed? Who should have access to the files, and how will access to them be controlled? How many copies of each CRF should be made? How should updated data be recorded on the original forms and on copies of them?
• Audits: What types of audits are useful? How much of the data should be audited? How should auditing results be interpreted? What changes should be made to processes based on the results of an audit?