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Add prescription drug data to skeleton

Source: R/add_rx.R
add_rx.Rd

Searches for specific drug codes (ATC or product names) in Swedish prescription registry data and adds corresponding boolean variables to the skeleton based on prescription periods and duration of treatment.

Usage

add_rx(
  skeleton,
  lmed,
  id_name = "lopnr",
  codes = list(rx_hormones_pubblock = c("L02AE", "H01CA")),
  source = "atc",
  rxs = NULL
)

Arguments

skeleton

A data.table containing the main skeleton structure created by create_skeleton

lmed

A data.table containing prescription registry data (LMED). Must have columns for person ID, prescription date (edatum), treatment duration (fddd), and drug codes (atc) or product names (produkt)

id_name

Character string specifying the name of the ID variable (default: "lopnr")

codes

Named list of drug code patterns. Names become column names in the skeleton; values are character vectors. Matching semantics depend on source (see below).

Prefixing a pattern with "!" turns it into a *row-level veto*: any prescription whose code matches the (un-prefixed) pattern is masked and does not contribute to the named output column. Final rule: a prescription row contributes to the named column iff at least one un-prefixed pattern matches AND no "!" pattern matches.

Behaviour notes worth knowing:

  • Vetoes are independent per named code. A "!" entry inside one list element does not leak into any other element of the same codes list. Two named codes can produce two completely different views of the same prescription rows.

  • Veto match style follows source. For source = "atc" the veto is prefix-based via startsWith(): "!N05AA" masks N05AA01, N05AA02, ... For source = "produkt" the veto is exact-match via %chin%: "!Sertralin" does NOT mask "Sertralin Sandoz" because product names are exact, not prefixes.

  • All-negative pattern set produces an empty column. c("!N05AA") on its own gives an all-FALSE result – without any positive pattern there is no set to carve from. Use a wider include + the negative, e.g. c("N05A", "!N05AA").

  • Per-(id, isoyearweek) aggregation respects the veto on a per-source-row basis. The veto removes specific prescription rows from the matched set before the per-week aggregation runs. If a person has both a vetoed Rx and a non-vetoed Rx whose coverage windows overlap in the same skeleton week, the non-vetoed Rx still drives that week to TRUE – the veto only kills its own row's contribution, not the whole week.

Examples:

  • c("N06A") – any antidepressant.

  • c("N05A", "!N05AA", "!N05AB") – any antipsychotic except first-generation typical agents.

Default includes hormone therapy codes for puberty blockers (L02AE, H01CA). Common patterns include:

  • Antidepressants: "N06A"

  • Hormone therapy: "G03", "L02AE", "H01CA"

  • Cardiovascular drugs: "C07", "C08", "C09"

source

Character string specifying search field and matching strategy:

  • "atc" (default) - Prefix matching in ATC codes (e.g., "N06A" matches "N06AB06"). Uses startsWith() for fast C-level matching.

  • "produkt" - Exact matching on product names (e.g., "Delestrogen" matches only "Delestrogen", not "Delestrogen Extra"). Uses %chin% for fast lookup.

rxs

Deprecated. Use codes instead.

Value

The skeleton data.table is modified by reference with prescription variables added. Variables are TRUE during periods when the prescription is active based on start/stop dates calculated from prescription date + treatment duration

See also

create_skeleton for creating the skeleton structure, add_diagnoses for diagnosis codes, add_operations for surgical procedures, make_lowercase_names for data preprocessing

Other data_integration: add_annual(), add_cods(), add_diagnoses(), add_icdo3s(), add_onetime(), add_operations(), add_quality_registry(), add_snomed3s(), add_snomedo10s()

Examples

# Load fake data
data("fake_person_ids", package = "swereg")
data("fake_prescriptions", package = "swereg")
swereg::make_lowercase_names(fake_prescriptions, date_columns = "edatum")

# Create skeleton
skeleton <- create_skeleton(fake_person_ids[1:10], "2020-01-01", "2020-12-31")

# Add prescription data
rx_patterns <- list(
  "antidepressants" = c("N06A"),
  "hormones" = c("G03", "L02AE")
)
add_rx(skeleton, fake_prescriptions, "p444_lopnr_personnr", rx_patterns, "atc")