Reducing the Effort of Building an eCRF
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Data is the linchpin for the billions of dollars dedicated to medical studies—and the eCRF is the main collection vehicle for that data. A high quality eCRF design is therefore as important as the data itself and requires extensive planning and attention to detail. The ideal features of an eCRF, like all good design, should facilitate both ease of use and high-quality results.
At its core, eCRF design should ensure:
- Optimal collection of data according to the study protocol
- Data collected is compliant
- Data meets all regulatory requirements
- Positive end user experience and user-friendly workflow
- Data export is seamless and readable by analytic tools
What are Some Important Design Practices?
eCRF design is a complex task, with a multitude of resources on the topic. Here are our top tips to streamline processes and maintain high quality:
- Create your eCRF specifications within a software design tool that allows eCRF build directly from the study protocol and provides the annotated CRF as an output.
- Build static forms first, then add edits. Experience has shown us that changes happen and the cost of these are minimal as long the edit checks have not been programmed yet.
- Limit your data validation plan to the most relevant edit checks to avoid the cost of over-programming your eCRF.
- Employ a thorough user acceptance testing (UAT) of the eCRF throughout the process. The first UAT should come after the static forms are built, again after the edit checks are incorporated, and prior to production.
- Remember to design for the end user, primarily the study site personnel, so consider them as your customers and think about their circumstances and needs.
- Use spell check – eliminating typos and other errors prior to production will avoid confusion (and embarrassment).
Design eCRFs Using Standards
There are two different types of standards: regulatory standards and your company’s internal standards. A well-designed eCRF should always comply with the major data and electronic standards and pave the way for regulatory submission.
The FDA released a Data Standards Catalog addressing submission data exchange and submission data terminology. The FDA and the PMDA have adopted Clinical Data Interchange Standards Consortium (CDISC) standards for both data exchange and submission data.
CDISC provides CDASH conventions to collect data consistently across studies to provide clear traceability of submission data into the Study Data Tabulation Model (SDTM). XClinical recommends using CDASH elements pre-mapped to the CDISC SDTM standard and that CDASH elements are combined on different pages to provide flexible eCRF form design.
There are major benefits to utilizing internal standards to create your eCRF. Reuse of forms such as Adverse Events, Concomitant Medication, Medical History, etc. will speed up trial design. Consistent use of factors such as metadata terminology, code lists, and eCRF layout will allow for faster and easier eCRF creation. Incorporating the regulatory standards into your internal standards will create efficiencies not only in the eCRF build but also with data extraction and analysis.
Design with the End in Mind
As you consider usability, also keep your eye on the prize. The ultimate purpose of the eCRF is to transport data from the research environment to the evaluation environment, which ultimately results in submission of data to regulatory authorities and its acceptance.
Prior to submission, the data will be reviewed, cleaned and analyzed by many stakeholders. The eCRF design should be well structured so reports can be easily created and understood. Additionally, the resulting SAS datasets should be well organized for the data management teams.
The best design incorporates standard eCRF pages from a library that smoothly moves your data from data collection to submission datasets and onto analysis datasets. Smart software systems provide a library that contains the SDTM mapping for standard eCRF pages. If you don’t use standard pages from a library, the next best practice would be to do your SDTM mapping before the study begins. This will ensure data is properly collected to create SDTM datasets and save valuable time at the end of the study.
Which eCRF Software Designer Tool is Right for Me?
Though it’s tempting to create an eCRF with the editing tools included in your office suite, it’s not ideal. In fact, the market provides a myriad of vastly superior eCRF software to design eCRFs, with feature sets that include software design tools. These tools can help jump start your eCRF design and creation via template libraries. As a result, you can customize existing, proven eCRFs, with built-in standards support and specifically-designed editors. When choosing eCRF software, it’s best to go for one that includes:
- An eCRF library
- The ability to meet all regulatory requirements
- Support for industry standards
- Functions that automate the creation of annotated CRF and data validation plan
- Ease of use and flexibility for the size / complexity of your clinical studies
- No prior programming knowledge, including cross form/cross visit edit checks
- Straight-forward version control for amendments.
Efficient eCRF design is integral to ensuring the success of any clinical research study and it impacts every moving part and component. Keeping our design tips in mind will make your eCRFs more effective by collecting consistent and valid data that requires fewer manual queries and meets regulatory compliance. Employing an effective design process can dramatically streamline workflows and better serve customers, as well as save time and lower costs.