Entering Data Should Be Easy – Avoid These Common Mistakes  

You did the research, compared features, and selected the right EDC for your study. Now what? Now you build out your database, the foundation for a successful study. But what does that look like? We can’t tell you what will work best for your organization, but we can warn you about these 5 common mistakes when developing an effective EDC database that helps make data entry easy for your clinicians.  

Mistake 1: Making it too complex.  

Solution: Eschew obfuscation.   

When building an EDC, it is important to remember that you will not be the only person using the platform. Site personnel, biostatisticians, monitors, data managers, and others will need to be able to navigate the EDC easily to use it effectively. Keep each viewpoint in mind during the duration of the study build. Avoiding confusion will ease the course of the study while keeping clinicians happy.     

Mistake 2: Adding too many constraints.  

Solution: Implement fewer error constraints.  

After building the form interface, builders often wonder “what constraints should I add?” Producing standard guidelines helps builders maintain consistency across forms, resulting in a clearer interface for study users. You would likely want to generate a “hard” error via a constraint when a visit date is missing on a form. Consider a “soft” error (a warning) if the weight entered fits outside of a normal, expected range. But let’s say you have a read-only field that contains the result of a calculation. No constraint is needed there.  

  

Mistake 3: Adding features because they exist.  

Solution: Add features that are needed.   

Features are great. They streamline data entry, automate edit checks, and generally can be really, really cool. But when there are too many unnecessary features, it can lead to the classic Jurassic Park Dilemma – I can… but should I? Features can be great for tech-savvy individuals, but not so great for clinicians trying to get through the paperwork and go home. Who wants to stop and learn a new computer skill every time they need to enter data? Anyone?  

  

Mistake 4: Collecting excess data.  

Solution: Only collect the necessary data.  

If the questions are simple, the answers will be simple. Only collect data that is relevant to your study. Unnecessary data can add confusion to what is needed and relevant. Ask for the moon, and you will be disappointed.   

  

Mistake 5: Failing to consider how the forms will be used by the sites.  

Solution: Broaden your focus.  

Focusing too narrowly on the monitoring and statistics of the data can be counterproductive. If you fail to consider how the data will be entered, it will end up making the resulting data more difficult to analyze. Keeping your sites in mind from the start of the study build will help encourage adherence to protocol requirements.  

Avoiding these 5 mistakes will allow you to build a productive study with minimal roadblocks. Stay away from complexity, too many restraints and features, unnecessary data, and remember site involvement to ensure data integrity throughout the study’s lifecycle. Happy Building! …on your own with our Study Builder or have Prelude build it for you.   

Interested in building a study with Prelude? Contact Us.