Afront-end checkis a type ofreal-time validationperformed at the point of data entry—typically within anElectronic Data Capture (EDC)system or data entry interface—designed to ensure that the data entered in a text box (or any input field) isvalid, logically correct, and within expected parametersbefore the user can proceed or save the record.
According to theGood Clinical Data Management Practices (GCDMP, Chapter on Data Validation and Cleaning),edit checksare essential components of data validation that ensure data accuracy, consistency, and completeness. Front-end checks are implemented within the data collection interface and are triggered immediately when data are entered. They prevent invalid entries (such as letters in numeric fields, out-of-range values, or improper date formats) from being accepted by the system.
Examples of front-end checks include:
Ensuring a numeric field accepts only numbers (e.g., weight cannot include text characters).
Validating that a date is within an allowable range (e.g., not before the subject’s date of birth).
Requiring mandatory fields to be completed before moving forward.
This differs fromback-end checksorprogrammed checks, which are typically run later in batch processes to identify data inconsistencies after entry.Manual checksare human-performed reviews, often for context or data that cannot be validated automatically (e.g., narrative assessments).
Front-end edit checks are preferred wherever possible because theyprevent errors at the source, reducing the number of downstream data queries and cleaning cycles. They contribute significantly todata quality assurance,regulatory compliance, andefficiency in data management operations.
Reference (CCDM-Verified Sources):
Society for Clinical Data Management (SCDM), Good Clinical Data Management Practices (GCDMP), Chapter: Data Validation and Cleaning, Section 6.2 – Edit Checks and Real-Time Data Validation
FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6 – Data Entry and Verification Controls
ICH E6 (R2) Good Clinical Practice, Section 5.5 – Data Handling and Record Integrity
CDISC Operational Data Model (ODM) Specification – Edit Check Implementation Standards
