Evaluating the Impact of Data Standardization on Real‐World Data
The data standardization refines the data (e.g., removes duplicate claims and variables or variable categories), which may reduce outliers and errors but yield lower distributions and counts of certain variables than observed in native format data. Therefore, it is critical to understand how standardization impacts the data and subsequently its fitness for use.
Authors
- Aloka Chakravarty (ORCID: https://orcid.org/0000-0003-2331-3053)
- Elizabeth M. Garry (ORCID: https://orcid.org/0000-0002-5871-1599)
- Tamar Lasky (ORCID: https://orcid.org/0000-0003-4104-394X)
- Donna R. Rivera (ORCID: https://orcid.org/0000-0002-4565-4556)
- Jennifer Duryea
- Priya Govil
- Aidan Baglivo
- Wei Liu (ORCID: https://orcid.org/0000-0002-0434-4674)
- Marie C. Bradley (ORCID: https://orcid.org/0000-0002-3231-9951)
Institutions
- United States Food and Drug Administration (US)
- Center for Drug Evaluation and Research (US)
- Aetion (United States) (US)
- Engineering Information Foundation (US)
Publication Details
- Journal
- Pharmacoepidemiology and Drug Safety
- Published
- 2025-08-01
- DOI
- https://doi.org/10.1002/pds.70191
- Citations
- 1
- Primary Topic
- Healthcare Policy and Management
- Type
- article
- Field-Weighted Citation Impact
- 3.13
Funders
- U.S. Food and Drug Administration