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Derived Elements

Derived tables are computed from raw clinical tables — they aggregate individual events into clinically meaningful periods. You don't record data into these tables directly; the ETL pipeline builds them.

Think of it this way: condition_occurrence has one row every time a diabetes diagnosis is recorded. condition_era collapses those into a single continuous period of "this patient had diabetes from X to Y."

  • Condition Era

    Continuous periods of a condition, aggregated from condition_occurrence using configurable gap logic (default: 30-day persistence window).

    Condition Era

  • Drug Era

    Continuous medication exposure periods, aggregated from drug_exposure at the ingredient level.

    Drug Era

  • Dose Era

    Periods of consistent daily dose for a drug, derived from drug_exposure with dose normalization.

    Dose Era

  • Episode / Episode Event

    Higher-level clinical constructs (treatment regimens, pregnancy episodes, disease courses) explicitly curated during ETL or by researchers.

    Episode Episode Event

Gap logic matters

Era tables use a persistence window to decide when gaps between events create a new era vs. extend an existing one. The default is typically 30 days, but this is configurable in the ETL. Always verify the gap logic used at your site before interpreting era durations.