Managing protocol changes in eCRF software
Electronic data capture is how a study collects structured information from participants. The electronic case report form is the unit of that collection, and in most programmes the gap between how a form is designed and how it reaches production is filled by manual work.
Manual work in clinical data capture
Research teams design in spreadsheets. Production needs versioned, validated, renderable forms. Someone has to bridge that, and usually it is a person copying question text, response options, and skip logic into a form builder by hand.
Definition
The questionnaire as the research team wrote it: questions, response types, options, ordering, and the conditions under which each question applies. Everything after it is generated from this definition, so it has to be the single source of truth.
Structured representation
The definition is parsed into a machine readable schema rather than re-entered by hand. Parsing removes transcription error and lets versions of the form be diffed.
Ingestion
The schema is loaded into the application's own data model as records, so the form is data the platform can query, version, and audit rather than code someone has to maintain.
Dynamic rendering
The participant facing form is rendered from those records at runtime. Adding or amending a question is a data change, not a release.
Clinical data capture automation
The obvious return is time. The more important one is consistency: a generated form matches its source definition exactly, every time, and the definition is the thing under version control. Transcription errors go away.
When deploying a revised questionnaire costs minutes, study teams fix protocol problems they would otherwise have lived with.
The approach applies wherever a study team authors questionnaires outside the platform that has to run them. The definition stays where the research team writes it, and everything downstream is generated from it.
Study rules and workflow automation →