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This vignette introduces a set of functions designed to manipulate and explore codelists within an OMOP CDM. Specifically, we will learn how to:
First of all, we will load the required packages and connect to a mock database.
library(DBI)
library(duckdb)
library(dplyr)
library(CDMConnector)
library(CodelistGenerator)
# Connect to the database and create the cdm object
con <- dbConnect(duckdb(),
eunomiaDir("synpuf-1k", "5.3"))
cdm <- cdmFromCon(con = con,
cdmName = "Eunomia Synpuf",
cdmSchema = "main",
writeSchema = "main",
achillesSchema = "main")
We will start by generating a codelist for acetaminophen
using getDrugIngredientCodes()
acetaminophen <- getDrugIngredientCodes(cdm,
name = "acetaminophen",
nameStyle = "{concept_name}",
type = "codelist")
Subsetting a codelist will allow us to reduce a codelist to only those concepts that meet certain conditions.
This function keeps only those codes observed in the database with at
least a specified frequency (minimumCount
) and in the table
specified (table
). Note that this function depends on
ACHILLES tables being available in your CDM object.
We will now subset to those concepts that have
domain = "Drug"
. Remember that, to see the domains
available in the cdm, you can use getDomains(cdm)
.
We can use the negate
argument to exclude concepts with
a certain domain:
We will now filter to only include concepts with specified dose
units. Remember that you can use getDoseUnit(cdm)
to
explore the dose units available in your cdm.
acetaminophen_mg_unit <- subsetOnDoseUnit(acetaminophen_drug, cdm, c("milligram", "unit"))
acetaminophen_mg_unit
As before, we can use argument negate = TRUE
to exclude
instead.
Instead of filtering, stratification allows us to split a codelist into subgroups based on defined vocabulary properties.
Now we will compare two codelists to identify overlapping and unique codes.
acetaminophen <- getDrugIngredientCodes(cdm,
name = "acetaminophen",
nameStyle = "{concept_name}",
type = "codelist_with_details")
hydrocodone <- getDrugIngredientCodes(cdm,
name = "hydrocodone",
doseUnit = "milligram",
nameStyle = "{concept_name}",
type = "codelist_with_details")
Compare the two sets:
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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