¶ … CFR-Case report form is the main unit of data compilation in every clinical trial. The model of the CRF design carries and directly influences the success or failure of this study. CRF-case report form is a special document in clinical researches. It ought to be driven by study protocol, rich in content and have necessary material to gather the research specific data. Though paper CRFs are widely in use, the use of electronic CRFs (eCRFS) is becoming more popular, as a result of the advantages they provide, like better data quality, online disparity management and swifter database lock (Bellary, Krishnankutty, & Latha, 2014).
Important Considerations in Designing a Paper CRF. How Do They Affect Data Management?
Managing Errors
Creating a paper CRF is a very dull job that could possibly lead to data errors and erroneous conclusions, which require careful attention to reduce replication of CRF pages. The chances of mistakes occurring while transferring data from the source document to the paper CRF are quite common. Furthermore, for researches with large size of samples, if conventional methods of data compilation through paper CRFs are used, manual data arrangement may give one serious concerns. To make reading/understanding and correct data entry easier, it is preferable to use an uncrowded CRF layout.
Putting a...
Putting several details on the same page gives the CRF a cluttered look, which makes the data entry more difficult, and eventually results to more discrepancies.
While designing CRF, the following points should be noted:
Using the same formats, font sizes and font style all through the CRF booklet
Provide separate lines or boxes to contain the answers. This tells the data recorder where to enter/write the answer and helps in giving it a visual differentiation from the entry fields for the other questions
Divide the columns using thick lines
Provide italicized and bold instructions
Reduce free text responses
Important Considerations in Designing an Electronic CRF. How Do They Affect Data Management?
User Training and System Validation
When dealing with ordinal data, to ensure clarity and uniformity among the raters, it is important to provide sufficient explanations adjacent the CRF fields. It is also necessary to avoid capturing the same data in different…
