Skip to contents

Add 2023 MHT exposure variables to a person-week skeleton

Source: R/lmed-v20230509.R
add_lmed_v20230509.Rd

Derives menopausal hormone therapy (MHT) exposure from Swedish prescription registry (LMED) data, using the definitions pinned for the 2023 MHT study. `add_lmed_v20230509()` categorises dispensed product names into MHT groups. It corrects the dispensed durations of products whose recorded defined daily doses are unreliable. It then derives the approach-based treatment variables.

Usage

add_lmed_v20230509(skeleton, lmed)

Arguments

skeleton

A `data.table` person-week skeleton with an integer `id` column and a character `isoyearweek` column of the form `"YYYY-WW"`. Modified by reference; see `Value`.

lmed

A `data.table` of dispensed prescriptions. The function reads exactly four columns:

  • `p1163_lopnr_personnr` - person identifier, matched against `skeleton$id`

  • `produkt` - product name

  • `edatum` - `Date` of dispensing

  • `fddd` - numeric dispensed duration in days

`lmed` is NOT modified. The function first subsets `lmed` to the identifiers present in `skeleton`, which allocates a new `data.table`. Every subsequent `:=` then writes to that internal subset. The caller's own `lmed` is left untouched.

Value

An internal logical flag, NOT the skeleton. You MUST NOT assign the result: `skel <- add_lmed_v20230509(skel, lmed)` would overwrite your skeleton with that flag. Call the function for its effect, then carry on using the object you passed in.

`skeleton` is MODIFIED BY REFERENCE. The caller's own object gains one logical column per MHT product category (`A1` ... `I2`) and the character columns `approach1`, `approach2` and `approach3`. If you still need the input skeleton unchanged, pass `data.table::copy(skeleton)`.

`lmed` is NOT modified. Only `skeleton` is modified in place.

Details

`add_lmed_v20230509()` performs several steps:

  • Restricts the LMED data to individuals present in `skeleton`

  • Categorises products into MHT groups (`A1` ... `I2`) from product names

  • Applies duration fixes for specific products (IUDs, minimum doses)

  • Flags the product categories in force in each person-week

  • Derives the approach variables, bridging gaps of up to four weeks

Note

This entry point is pinned to the 2023 study definitions. It flags the product categories with a nested loop over categories and ISO weeks. It reads the LMED identifier from `p1163_lopnr_personnr`. It has no `verbose` argument: it always reports progress with `message()`.

See also

[add_lmed_v20250909()] for the 2026 definitions, and [fake_lmed_2023] and [fake_skeleton_mht] for the synthetic fixtures used below.

Other MHT exposure entry points: add_lmed_v20250909(), add_lmed_v20260828()

Examples

library(data.table)
#> 
#> Attaching package: ‘data.table’
#> The following object is masked from ‘package:base’:
#> 
#>     %notin%

# copy() the skeleton: it is modified in place. `lmed` is not modified,
# but copy() it too so the shipped fixture is never altered by accident.
skeleton <- copy(fake_skeleton_mht)
lmed <- copy(fake_lmed_2023)

suppressMessages(add_lmed_v20230509(skeleton, lmed))
#> [1] FALSE

# `skeleton` itself now carries the derived columns
skeleton[, .N, keyby = .(approach1)]
#> Key: <approach1>
#>            approach1     N
#>               <char> <int>
#> 1: local_or_none_mht  4773
#> 2:      systemic_mht   843