Skip to content

Study Reveals Widespread Modifications to US Federal Health Datasets

A recent study exposes widespread modifications to US federal health datasets. The changes, often unnoticed and undocumented, raise questions about data reliability and the need for stronger transparency measures.

This is a paper. On this something is written.
This is a paper. On this something is written.

Study Reveals Widespread Modifications to US Federal Health Datasets

A recent study published in The Lancet has uncovered significant modifications to federal health datasets in the United States. Key agencies like the Department of Health and Human Services, Centers for Medicare and Medicaid Services, Food and Drug Administration, and Centers for Disease Control and Prevention have altered data involving medical casework, drug applications, and public health surveillance. This includes data related to disease outbreaks and vaccinations, which was impacted during the government shutdown.

The changes coincide with a January 20 presidential directive instructing federal agencies to use the term 'sex' instead of 'gender'. The study reveals a surge in data alterations since January, with 4% of changes happening in late January and a significant 72% occurring in March. In most cases, the word 'gender' was replaced with 'sex' in the altered datasets. However, only 15 of these datasets included a note about the modification.

Undocumented changes to existing data can erode confidence in government statistics and skew research. The study found alterations across multiple federal agencies, including the Department of Veterans Affairs and the Centers for Disease Control and Prevention. Researchers and journalists have been monitoring changes to government websites and documenting the disappearance of federal health data for months.

The study highlights the need for stronger transparency measures to safeguard data integrity. The authors call for independent archiving and international alternatives to ensure the reliability of federal health data. Nearly half of the analyzed datasets were altered, and most lacked a notice or log about the change. This underscores the importance of robust data governance to maintain public trust in government statistics.

Read also:

Latest