Glossary

What is Temporal drift?

Updated September 1, 2026

Temporal drift is the decay of a data record's accuracy over time. A medication list from 2019, an address from a prior enrollment, or last quarter's risk factor may be dangerously wrong today while still looking perfectly clean. Data does not announce that it has expired.

Drift is modality-specific: a CBC result ages differently than a continuous heart-rate stream, and an allergy list ages differently than a genomic record. The Data Trust Index scores Recency with time-decay calibrated per modality, so the score reflects the record's currency at the moment of inference, not the moment of capture.

Models that ignore temporal decay produce inferences that are technically valid and clinically misleading, which is why drift is one of the five barriers the trust layer exists to remove.