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5 Best Practices For Annotated CRF SDTM


An annotated case report form (aCRF) provides a means for the clinical team to understand how data will be captured in the electronic case report form (eCRF). It helps during the management of data collected from study sites. The annotated CRF is usually created after the eCRF has been developed.

However, if necessary, an annotated CRF can be created during study design and development. Thus, a well-written automated CRF can help streamline various aspects of clinical trial execution by creating a shared understanding among stakeholders.

What’s The Objective Of Having An Annotated CRF?

The objective of having an annotated CRF is to help the clinical team understand how the data will be captured in the eCRF. An annotated CRF should be readable and user-friendly. It should have essential details about field labels, required fields, mandatory vs. non-mandatory fields, default values, and field units.

In addition to providing this information for each study variable, it may also include coding specifications for Study Data Tabulation Model (SDTM) variables collected for the study. It should also have other relevant information about these variables, such as whether they’re intended for quantitative or qualitative analysis; or whether one or two modalities provide them.

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Now, what are the best practices your organization should adhere to?

It Should Be Meaningful In Its Own Right

While it’s true that the analyst will use the SDTM, this is only one of many users. For example, business users will likely want to print the CRF for use offline or on mobile devices. They may also need to generate reports or create graphical representations of responses. You should ensure that your annotated CRF is easy to read, understand, and use. You can also confirm if you can update text easily should requirements change and if you can print individual pages without overlapping issues.

It Should Have Cross-References Wherever Necessary

Cross-references are essential to ensuring that the CRF data files are consistent with each other. For example, suppose you cross-reference a field in your participant information and their answer to a survey question. In that case, this will help you track which participant patiently answered what question. You can also use them to keep track of other relationships between fields that may be important for analysis or reporting purposes. You can even take a cue from how other companies streamline their drug processes.

Necessary Information Should Not Be Separated From Each Other

Information should be grouped logically. If the information is grouped by topic, there’s a section that can be separated into subtopics. If you’re grouping by section, each paragraph should have a header and explain what the paragraph is about.

If you’re using any annotation fields in your document, such as questions or answers for the capture form field, these annotations should be grouped based on their corresponding fields from STDM tables. This will help improve usability. It’ll allow readers to quickly find relevant portions of the content without going through every word of your document line-by-line searching for specific data points.

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Annotated CRF Should Have Other Essential Details

These details could include field labels, required fields, mandatory vs. non-mandatory fields, default values, and field units. Field labels should be clear and concise. The user is likely to be familiar with the domain of the data being collected but not necessarily the exact terminology used for a particular field (e.g., ‘disability’ instead of disability type). It’s also important to consider whether your participants will understand abbreviations or other uncommon words you use as part of your labels.

Required fields should be marked; otherwise, some respondents may enter erroneous information or leave it blank. If you want respondents to answer questions about their income level, education status, or any other wholly and accurately, ensure they know how important it is.

Mandatory vs. non-mandatory questions should also be identified so respondents know what’s required and optional when completing your survey. For example: ‘Are you currently pregnant?’ versus ‘Do you plan on having children in the next few years?’

It Must Include Coding Specifications For SDTM Variables That Are Being Collected For The Study

SDTM variables, such as demographics and health history, are collected for the study. They’re used to collect and store the data from participants during the survey administration process. In other words, these coded values represent how you want to record data about your research participants to hasten up analysis.


An annotated CRF is a valuable tool that shouldn’t be overlooked when creating studies. Not only does it help you understand how the data will be captured in the eCRF, and it provides a visual representation of what your study participants will have to complete by way of questions, checkboxes, and dropdowns. The annotated CRF should be readable and user-friendly and contain essential details, including field labels, required fields, and mandatory versus non-mandatory fields.

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