Despite its importance, data standardization in epidemiology faces several challenges:
Diverse Data Sources: Epidemiological data often comes from a wide range of sources, including surveys, electronic health records, and laboratory tests, each with its own format and standards. Data Completeness: Incomplete data can complicate the standardization process, as missing values may need to be imputed or handled in a consistent manner. Resource Intensive: Standardizing data can be time-consuming and requires significant expertise, especially when dealing with large and complex datasets.
