Case report forms (CRFs) lie at the very center of data collection in medical research. A well-designed CRF can either make or break a research project. From data quality to participants’ experiences, it affects everything.

This article will discuss the core strategies that can help in good CRF design, which can smoothen the research process and boost study outcomes. Read on for more information.

The Foundation of CRF Design

To develop a strong CRF, it’s important to know what the study seeks to establish and what data points are essential. Knowing this, researchers can do away with irrelevant fields and keep away from cluttered forms.

It’s also essential to have a clear layout. Have the questions arranged in a sequence and group-related ones. This will be convenient for both the researchers and the participants to go through quickly. Also, use a combination of different types of questions: multiple choice (for simple data), open-ended, and detailed.

Don’t know where to start? You can always count on an expert guide to CRF design. And here’s the good news: there are platforms that offer these guides for free!

Keeping Language Clear and Concise

Jargon can confuse participants, leading to inaccurate responses. Use plain language whenever possible. If technical terms are unavoidable, provide clear definitions.

For example, ask, ‘Did you have any unanticipated side effects or medical issues following drug use?’ instead of, ‘Did you encounter any adverse events?’

This way, the forms are renderable and user-friendly, especially for studies involving the general public rather than medical professionals.

Design for Data Quality

Quality data is the main objective of all clinical trials, and a good CRF design will take this into account. Here’s how to go about it:

Built-In Validation

Add checks that flag impossible or unlikely answers. It could be as simple as ensuring the legitimacy of a date of birth or more complex like cross-referencing related questions.

Skip Logic

Use conditional questions to avoid irrelevant sections. For instance, only ask about pregnancy symptoms if the participant has indicated they’re pregnant.

Standardized Responses

Where possible, use pre-defined answer choices. This makes data analysis much easier later on.

Clear Instructions

Provide guidance on how to answer each question type. This is especially important for more complex data entry, like recording medication dosages.

Balancing Depth and Participant Burden

Researchers often aim to gather as much data as possible. However, CRFs that are too lengthy and/or too complicated can cause participant fatigue and dropout. The trick is to strike the correct balance.

Start with prioritizing questions. What information is absolutely necessary for the study’s primary objectives? What’s ‘nice to have’ but not essential? Be ruthless in cutting anything that doesn’t directly contribute to the research goals.

Moreover, long questionnaires can always be split into several sessions. This can save respondents from questionnaire fatigue, especially for designs that require repeated administration.

Optimizing Multiple Data Collection Methods

CRFs aren’t universal. The design should be informed by how the collection will be made. There are considerations for paper forms and for forms to be collected using electronic data capture (EDC) and mobile apps.

For paper forms:

• Easy-to-read font
• Space to write the answer (free text)
• Question order is important, and jumping around is tricky.

For electronic forms:

• Leverage autofill and validation of data.
• User interface must be friendly to devices.
• Plan for data collection even when access to the internet may fail.

Mobile-specific considerations:

• Design for smaller screens with larger touch targets.
• Use progressive disclosure to show only relevant questions.
• Take advantage of device features like cameras for capturing images or barcodes.

No matter which method you choose, the key is to make the form easy and comfortable for people to use so they can give accurate information without getting frustrated.

Piloting and Iteration

Despite an elaborate pre-testing of a CRF, actual field testing is needed. It’s essential to pilot the form among a small subgroup of respondents similar to your target population. This can reveal issues that weren’t apparent on paper.

Watch out for:

• Time taken to fill the form
• Questions that pose problems
• Technical difficulties on screen

Use this feedback to refine the CRF and make some improvements before you launch your full study. Make changes. And note that it’s much better to catch a problem early on than find out that your major data collection tool is flawed halfway through your study.

Ensuring Regulatory Compliance

Clinical research is a highly regulated activity, and CRFs need to meet specific regulatory requirements. Check relevant guidelines—these likely refer to the FDA or EMA, depending on where the study is being conducted.

A few of the many important areas of compliance are:

• Non-clinical lab studies that support the clinical research
• Appropriate and correctly worded documentation of informed consent
• Methods for storage and transfer of data that will be secure
• An audit trail of what was done to the data

Experienced clinical professionals or a trusted partnership with an EDC provider should help navigate CRF writing.

Keep Data Analysis in Mind Throughout the CRF Design

The end goal of data collection is analysis. CRF design should keep this in mind from the start. Work with statisticians or data analysts early in the process to ensure the collected data will be suitable for the planned analyses.

Consider these examples:

• Coding schemes for categorical data
• Proper scales for numerical data
• Methods for handling missing data

A well-designed CRF dramatically eases the analysis phase, saves time, and reduces error.

Conclusion

CRFs are so critical to medical research, but they’re so often neglected. Make a form clear and simple to use, and the study proceeds harmoniously.

All the best CRFs will extract the necessary information without unnecessarily taxing the subjects’ patience. They’re easy to learn and serve their purpose.

While it takes effort to make good CRFs, it’s worth it. They lead to better data and stronger research results. By using these tips, researchers can make their studies work better and achieve more.