Building route-specific RxCUI and NDC lists

Overview

A common use case for rxref is to develop a list of RxNorm product concepts and National Drug Codes (NDCs) for a drug class.

For example, suppose we want to identify product RxCUIs and active NDCs for oral beta-blockers. This is not as simple as searching for beta-blocker ingredients and mapping everything to NDCs, because some beta-blockers are available through multiple routes.

For example:

metoprolol, atenolol, labetalol, propranolol, and sotalol may have oral and injectable products.
esmolol is injectable only.
timolol, betaxolol, and related drugs may have ophthalmic products.

For many pharmacoepidemiologic studies, we may want oral outpatient-use products only.

This vignette walks through a tidy workflow for:

resolving drug names to ingredient RxCUIs;
expanding ingredient RxCUIs to product RxCUIs;
filtering product RxCUIs by route; and,
mapping the filtered product RxCUIs to active NDCs.

Define a beta-blocker ingredient list

In this example, we start with generic drug names. In future versions of rxref, class-level helpers may make this step more automated. For now, users can supply a curated ingredient list for the class of interest.

library(rxref)
library(dplyr)
library(purrr)

beta_blocker_names <- c(
  "acebutolol",
  "atenolol",
  "betaxolol",
  "bisoprolol",
  "carvedilol",
  "labetalol",
  "metoprolol",
  "nadolol",
  "nebivolol",
  "penbutolol",
  "pindolol",
  "propranolol",
  "sotalol",
  "timolol"
)

Resolve drug names to ingredient RxCUIs

First, use find_ingredients() to resolve each drug name to an RxNorm ingredient concept.


bb_ingredients <- find_ingredients(beta_blocker_names) |>
  filter(tty == "IN") |>
  distinct(
    input,
    ingredient_rxcui = rxcui,
    ingredient_name = name
  )

bb_ingredients

The resulting table contains one row per resolved ingredient. These ingredient RxCUIs are the starting point for product expansion.

Expand ingredients to product RxCUIs

Next, use products_for_ingredients() to identify product-level RxNorm concepts containing each ingredient.


bb_products <- products_for_ingredients(
  bb_ingredients$ingredient_rxcui,
  include_combos = TRUE
) |>
  left_join(bb_ingredients, by = "ingredient_rxcui")

bb_products

By default, this returns product-level RxNorm concepts such as clinical drugs and branded drugs. Because include_combos = TRUE, combination products are retained. For beta-blockers, this means products such as beta-blocker/thiazide combinations may be included.

To exclude combination products, set:


bb_single_ingredient_products <- products_for_ingredients(
  bb_ingredients$ingredient_rxcui,
  include_combos = FALSE
)

bb_single_ingredient_products

Why route filtering matters

At this point, the product list may include products from multiple routes. For example, some beta-blockers have oral tablets, injectable products, or ophthalmic solutions.

We can use get_clinical_attributes() to inspect route information for the product RxCUIs.


bb_attrs <- get_clinical_attributes(
  unique(bb_products$product_rxcui)
)

bb_attrs |>
  count(route, dose_form_group, sort = TRUE)

This helps verify whether the product list includes routes that are outside the intended use case.

Filter to oral products

To keep only orally available products, use filter_products_by_route().


bb_oral_products <- bb_products |>
  filter_products_by_route(route = "ORAL")

bb_oral_products

The returned table keeps product-level metadata and appends summarized route and dose-form information.


bb_oral_products |>
  count(routes, dose_form_groups, sort = TRUE)

This should retain products such as oral tablets, capsules, and oral solutions, while excluding injectable or ophthalmic products.

Map oral product RxCUIs to active NDCs

Once the product list is restricted to oral products, use map_products_to_ndcs() to map the product RxCUIs to NDCs.


bb_oral_ndcs <- map_products_to_ndcs(
  bb_oral_products,
  status = "ACTIVE"
)

bb_oral_ndcs

The output is a flat tibble with one row per product RxCUI/NDC pair. Product metadata is retained alongside the NDC.


bb_oral_ndcs |>
  select(
    ingredient_name,
    product_rxcui,
    product_name,
    product_tty,
    routes,
    dose_forms,
    ndc11,
    ndc_status
  )

Summarize the resulting list

For quality control, it is useful to summarize the number of products and NDCs by ingredient.


bb_oral_products |>
  count(ingredient_name, sort = TRUE, name = "n_product_rxcuis")

bb_oral_ndcs |>
  count(ingredient_name, sort = TRUE, name = "n_active_ndcs")

You may also want to inspect combination products separately.


bb_oral_products |>
  filter(n_ingredients > 1) |>
  select(
    ingredient_name,
    product_rxcui,
    name,
    tty,
    n_ingredients,
    routes,
    dose_forms
  )

A shortcut using search_drug()

The same workflow can be run more compactly with search_drug().

To return oral product RxCUIs only:


bb_oral_rxcuis <- search_drug(
  beta_blocker_names,
  return = "rxcui",
  route = "ORAL",
  include_combos = TRUE
)

bb_oral_rxcuis

To return a flat table of oral product RxCUIs and active NDCs:


bb_oral_ndcs2 <- search_drug(
  beta_blocker_names,
  return = "ndc",
  route = "ORAL",
  ndc_status = "ACTIVE",
  include_combos = TRUE
)

bb_oral_ndcs2

This is the most direct workflow when the goal is a usable product RxCUI/NDC table.

Returning both products and NDCs

If you want both the unique product RxCUI table and the expanded NDC table, use return = "both".


bb_oral_both <- search_drug(
  beta_blocker_names,
  return = "both",
  route = "ORAL",
  ndc_status = "ACTIVE",
  include_combos = TRUE
)

names(bb_oral_both)

bb_oral_both$products

bb_oral_both$ndcs

This returns a list because the two tables have different grains:

products: one row per product RxCUI;
ndcs: one row per product RxCUI/NDC pair.

Suggested QC checks

When developing a study-specific medication list, it is good practice to review the resulting concepts before finalizing the cohort definition. Even if the package is working correctly, there are on occasion errors in RxNorm itself.

The following are some examples.

Check whether any non-oral product names remain


bb_oral_products |>
  filter(grepl(
    "Injection|Injectable|Ophthalmic|Topical|Transdermal|Nasal|Inhalation",
    name,
    ignore.case = TRUE
  ))

Check the observed routes and dose-form groups


bb_oral_products |>
  count(routes, dose_form_groups, sort = TRUE)

Check combination products

Depending on the scientific question, combination products may be appropriate to include or exclude.


bb_oral_products |>
  filter(n_ingredients > 1) |>
  count(ingredient_name, sort = TRUE)

Summary

This vignette demonstrated how to build a route-specific medication list, with oral beta-blockers as an example, using rxref.

The key steps are:

find_ingredients() to resolve drug names to ingredient RxCUIs;
products_for_ingredients() to expand ingredients to product RxCUIs;
filter_products_by_route() to retain products for the route of interest;
map_products_to_ndcs() to obtain NDCs; OR,
search_drug() for a compact end-to-end workflow.

For drug classes with products available through multiple routes, route filtering is an important quality-control step before mapping to NDCs or using the resulting list in pharmacoepidemiologic analyses.

Steven Smith