In this post, we touch upon a few elements that can help you design a good Electronic Case Report Form (eCRF).
Over the years we have assisted several organizations in designing eCRFs. Therefore, we have curated seven principles behind a good eCRF.
Design better forms, save time and lower costs
From our experience, studies with well-designed forms perform better, compared to those that electrify paper. Not only are forms better received by participants, but have also proven to increase compliance and data quality.
With better-designed forms, we’ve seen increased compliance rates, better data quality, and better communication between study participants. This has lead to decreased time spent on data management, which results in lowered costs, and eventually shorter time to market.
Paper forms vs eCRFs
Paper has some notable qualities which support its claim for the golden standard of data collection, but it does have several drawbacks. Drawbacks that can make the transition to a digital medium more desirable.
The move from a paper-based case report form (CRF) to an electronic case report form (eCRF) can be a challenge. This is due to the inherent differences between paper and the computer as mediums.
Yet, the worst thing we can do, when transitioning to an eCRF is to electrify paper. Meaning, copying the design directly into the eCRF, making the two look identical and calling it a day.
Not all forms are paper-based
Traditional CRFs are not always printed. People have been using Word, Excel, or other common digital solutions, as data collection methods. Such solutions have their drawbacks as well. You can learn why you should avoid using such solutions from our post on “Are we breaking the law by using Excel in Medical R&D”
The 7 principles behind a good eCRF
We identify 7 principles behind a good eCRF design process and want to exemplify how you can apply them to your own form design.
Here are the first three principles:
1. Eliminate uncertainty
Make the questions explicit. Never ask ‘If yes, check this box’. Create a Yes and No question to eliminate any uncertainty.
2. Request data with required fields
Make use of a mandatory setting. With some eCRFs, you can require people to input data or answer questions. This can be useful to remind people to complete a field or to hinder subsequent data input. This can also eliminate deliberate or accidental missing data. Yet, forcing people to complete a field can be sketchy as well. If data is not available, it can be difficult to force a person to input any value. Thus, allowing people to mark certain fields as ‘missing’ or ‘not available’ can be beneficial.
3. Acquire more quantifiable and less irrelevant data
Avoid free-text questions and use pre-defined options instead. Free-text is difficult to quantify and requires data cleaning. You won’t need to clean data if your forms are well-designed.
In most cases, a data collector, or a study coordinator already have an idea of the answers to expect. This knowledge should be utilised. One way is to use a multiple-choice question and define expected answers as possibilities. For cases where it’s not applicable, one of the possibilities can be ‘other’ and you can use a text field to capture the applicable answer.
You can access the remaining principles by downloading our white paper.
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It’s important to note that these principles are not definite rules. They are a reference from our own experience working with medical device manufacturers and clinical research organizations.
Every study is different, and the complexity of data collection varies greatly from one to another.
However, keeping these principles in mind can help improve the overall efficiency, and lower costs of R&D – which leads to a shorter time to market.