What practice ensures that only proper codes are used in data fields?

The concept that ensures only proper codes are used in data fields is rooted in the practice of range edit checks. Range edit checks involve establishing parameters or a predefined set of criteria that the data must adhere to. This process helps identify any coding errors or values that fall outside of expected ranges.

In the context of tumor registries and cancer data, it is crucial that the codes entered for diagnoses, treatments, or outcomes conform to established coding standards. Range edit checks can effectively flag any discrepancies by validating that the codes used fall within acceptable limits or categories, thereby ensuring the integrity of the data.

While data normalization, data validation, and quality assurance are related concepts aimed at improving the accuracy and reliability of data, they do not specifically focus on limiting the codes to only those that are appropriate for data fields in the same targeted way that range edit checks do. Data validation checks the accuracy and legitimacy of data entries, but may not directly limit them to a specific range of acceptable codes, while quality assurance encompasses a broader scope of practices intended to maintain overall data quality.