Combine two cohorts with set operations

Combines two existing server-side cohort tables using a set operation (intersection, union, or set difference). The result is assigned as a new server-side symbol that can be used in subsequent queries or plan executions.

Usage

ds.omop.cohort.combine(
  op,
  cohort_a,
  cohort_b,
  new_name = NULL,
  symbol = "omop",
  conns = NULL
)

Arguments

op

Character; the set operation to apply. One of "intersect" (patients in both cohorts), "union" (patients in either cohort), or "setdiff" (patients in cohort_a but not cohort_b).

cohort_a

Server-side cohort TABLE name for the first cohort (the value returned by ds.omop.cohort.create()), its dsomop_cohort_handle, or a cohort definition ID (integer).

cohort_b

Server-side cohort TABLE name for the second cohort (the value returned by ds.omop.cohort.create()), its dsomop_cohort_handle, or a cohort definition ID (integer).

new_name

Character; TABLE name for the combined result. If NULL (the default), an auto-generated name is used.

symbol

Character; the session symbol used when the OMOP connection was initialised (default: "omop").

conns

DSI connection object(s). If NULL (the default), the connections stored in the active session are used.

Value

Invisibly; a dsomop_cohort_handle carrying the server-side TABLE name for the combined cohort. The handle can itself be passed as cohort_a / cohort_b to a further ds.omop.cohort.combine().

Disclosure control

Each input is resolved + re-gated server-side, and the COMBINED result is gated on its distinct-subject count: if an operand is unavailable (absent/sub-threshold cohort_definition_id) or the combination yields fewer than the server's per-subset threshold (nfilter_subset) persons, the call FAILS CLOSED and no result table is materialised. An "insufficient individuals" error here reflects the operands/operation you chose and carries no disclosure about any pre-existing cohort.

Examples

if (FALSE) { # \dontrun{
diabetes <- ds.omop.cohort.create(spec = ..., cohort_id = 1)
hypertension <- ds.omop.cohort.create(spec = ..., cohort_id = 2)
# Patients with both diabetes AND hypertension
combined <- ds.omop.cohort.combine(
  op = "intersect",
  cohort_a = diabetes,
  cohort_b = hypertension
)
} # }