Package 'CodelistGenerator'

Title: Identify Relevant Clinical Codes and Evaluate Their Use
Description: Generate a candidate code list for the Observational Medical Outcomes Partnership (OMOP) common data model based on string matching. For a given search strategy, a candidate code list will be returned.
Authors: Edward Burn [aut, cre] (ORCID: <https://orcid.org/0000-0002-9286-1128>), Marta Alcalde-Herraiz [aut] (ORCID: <https://orcid.org/0009-0002-4405-1814>), Martí Català [aut] (ORCID: <https://orcid.org/0000-0003-3308-9905>), Xihang Chen [aut] (ORCID: <https://orcid.org/0009-0001-8112-8959>), Nuria Mercade-Besora [aut] (ORCID: <https://orcid.org/0009-0006-7948-3747>), Mike Du [aut] (ORCID: <https://orcid.org/0000-0002-9517-8834>), Danielle Newby [aut] (ORCID: <https://orcid.org/0000-0002-3001-1478>)
Maintainer: Edward Burn <[email protected]>
License: Apache License (>= 2)
Version: 4.0.2
Built: 2026-05-28 10:06:22 UTC
Source: https://github.com/darwin-eu/codelistgenerator

Help Index

Add concepts to a codelist

Description

Add concepts to a codelist

Usage

addConcepts(x, cdm, concepts, codelistName = NULL)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
concepts

Concepts_ID to add
codelistName

Name or names of codelist in x. If NULL, all codelist present in x will be considered.

Value

A codelist

Examples

library(omock)
library(CDMConnector)

# Creating CDM object
cdm <- mockCdmFromDataset(datasetName = "GiBleed")

# Creating codelist
codelist <- getDrugIngredientCodes(cdm,
                                   nameStyle = "{concept_name}")

# Add a concept to all the codelists:
codelist$acetaminophen
codelist <- codelist |>
 addConcepts(cdm, concepts = c(1L))
codelist$acetaminophen

# Add a concept to a specific codelist
codelist$amiodarone
codelist <- codelist |>
  addConcepts(cdm, concepts = c(2L), codelistName = "amiodarone")
codelist$amiodarone

# See function: `excludeConcepts()` for details on how to remove specific concepts
# from a codelist

Coerce to a codelist

Description

Coerce to a codelist

Usage

asCodelist(x, ...)

## S3 method for class 'codelist'
asCodelist(x, ...)

## S3 method for class 'codelist_with_details'
asCodelist(x, ...)

## S3 method for class 'concept_set_expression'
asCodelist(x, cdm, ...)

## S3 method for class 'candidate_codes'
asCodelist(x, ...)

Arguments

x

Only codelist_with_details and candidate_codes are currently supported.
...

For extensibility
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).

Value

codelist

Examples

library(omock)
library(CDMConnector)

# Creating CDM object
cdm <- mockCdmFromDataset(datasetName = "GiBleed")

# Create codelist from a codelist_with_details
codelist <- getDrugIngredientCodes(cdm,
                                   name = "acetaminophen",
                                   nameStyle = "{concept_name}",
                                   type = "codelist_with_details")

asCodelist(codelist)

# Create codelist from a candidate_codes
codelist <- getCandidateCodes(cdm,
                              keywords = "arthritis")

asCodelist(codelist)

Coerce to a codelist with details

Description

Coerce to a codelist with details

Usage

asCodelistWithDetails(x, cdm, ...)

## S3 method for class 'codelist_with_details'
asCodelistWithDetails(x, ...)

## S3 method for class 'codelist'
asCodelistWithDetails(x, cdm, ...)

## S3 method for class 'candidate_codes'
asCodelistWithDetails(x, cdm, ...)

Arguments

x

Only codelist and candidate_codes are currently supported.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
...

For extensibility

Value

codelist

Examples

library(omock)
library(CDMConnector)

# Creating CDM object
path <- downloadMockDataset(datasetName = "GiBleed",
                            path = NULL,
                            overwrite = NULL)
cdm <- mockCdmFromDataset(datasetName = "GiBleed")

# Create codelist_with_details from a codelist
codelist <- getDrugIngredientCodes(cdm,
                                   name = "acetaminophen",
                                   nameStyle = "{concept_name}",
                                   type = "codelist")

asCodelistWithDetails(codelist, cdm)

# Create codelist from a candidate_codes
codelist <- getCandidateCodes(cdm,
                             keywords = "arthritis")

asCodelistWithDetails(codelist)

Coerce to a concept set expression

Description

Coerce to a concept set expression

Usage

asConceptSetExpression(x, ...)

## S3 method for class 'codelist'
asConceptSetExpression(x, ...)

## S3 method for class 'codelist_with_details'
asConceptSetExpression(x, ...)

Arguments

x

Codelist or codelist with details
...

For extensibility

Value

codelist

Examples

library(omock)
library(CDMConnector)

# Creating CDM object
cdm <- mockCdmFromDataset(datasetName = "GiBleed")

# Create concept_set_expression from a codelist
codelist <- getDrugIngredientCodes(cdm,
                                   name = "acetaminophen",
                                   nameStyle = "{concept_name}",
                                   type = "codelist")

asConceptSetExpression(codelist)

# Create concept_set_expression from a codelist_with_details
codelist <- getDrugIngredientCodes(cdm,
                                   name = "acetaminophen",
                                  nameStyle = "{concept_name}",
                                   type = "codelist_with_details")

asConceptSetExpression(codelist)

Get the concept classes associated with a codelist

Description

Get the concept classes associated with a codelist

Usage

associatedConceptClassIds(x, cdm, standardConcept = "Standard", domain = NULL)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.
domain

Character vector with one or more of the OMOP CDM domains. The results will be restricted to the given domains. Check the available ones by running availableDomains(). If NULL, all supported domains are included: Condition, Drug, Procedure, Device, Observation, and Measurement.

Value

The concept classes

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmFromDataset(datasetName = "GiBleed")

# Get concept_class_ids in a codelist
x <- newCodelist(list("codes1" = c(1118088L, 40213201L, 35208414L),
                      "codes2" = c(1557272L, 4336464L, 4295880L)))
associatedConceptClassIds(x, cdm,
                         standardConcept = "Standard")

# Notice that this corresponds to the information provided by `concept_class_id`
# column in the `concept` table

Get the domains associated with a codelist

Description

Get the domains associated with a codelist

Usage

associatedDomains(x, cdm, standardConcept = "Standard")

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.

Value

A vector with the domains of the cdm.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all domains available in a codelist
codelist <- newCodelist(list("codes1" = c(194152L, 1830279L, 40558872L),
                             "codes2" = c(44022939L)))
associatedDomains(x = codelist, cdm = cdm,
                 standardConcept = c("Non-standard", "Standard"))

Get the dose forms associated with drug concepts in a codelist

Description

Get the dose forms associated with drug concepts in a codelist

Usage

associatedDoseForms(x, cdm)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).

Value

The dose forms available for drug concepts.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all dose forms available in a codelist
codelist <- newCodelist(list("codes1" = c(194152L, 1830279L, 40558872L),
                             "codes2" = c(44022939L)))
associatedDoseForms(x = codelist, cdm = cdm)

Get available dose units

Description

Get the dose units associated with a codelist

Usage

associatedDoseUnits(x, cdm, standardConcept = "Standard")

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.

Value

A character vector with available routes.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

codelist <- newCodelist(list("codes1" = c(194152L, 1830279L, 40558872L),
                             "codes2" = c(44022939L, 1830282L)))
associatedDoseUnits(cdm = cdm,
                   x = codelist)

Get the names of drug ingredients associated with codelist

Description

Get the names of drug ingredients associated with codelist

Usage

associatedDrugIngredients(x, cdm, standardConcept = "Standard")

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.

Value

A vector containing the concept names for all ingredient level codes found in the concept table of cdm.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all drug ingredients associated with a codelist
codelist <- newCodelist(list("codes1" = c(37498042L),
                             "codes2" = c( 42899580L, 35741956L)))
associatedDrugIngredients(x = codelist, cdm = cdm,
                         standardConcept = c("Standard", "Non-standard"))

Get available relationships with concepts in a codelist

Description

Get available relationships with concepts in a codelist

Usage

associatedRelationshipIds(
  x,
  cdm,
  standardConcept1 = "Standard",
  standardConcept2 = "Standard",
  domains1 = "Condition",
  domains2 = "Condition"
)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept1

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.
standardConcept2

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.
domains1

Character vector with one or more of the OMOP CDM domain. If NULL, all domains are considered.
domains2

Character vector with one or more of the OMOP CDM domain. If NULL, all domains are considered.

Value

A character vector with unique concept relationship values.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()


codelist <- newCodelist(list("codes1" = c(8479L, 4117795L),
                             "codes2" = c(8480L, 8600L, 8481L, 4189167L)))
associatedRelationshipIds(x = codelist, cdm = cdm,
                         standardConcept1 = c("Standard", "Non-standard", "Classification"),
                         standardConcept2 = c("Standard", "Non-standard", "Classification"),
                         domains1 = NULL,
                         domains2 = NULL)

Get drug routes associated with a codelist

Description

Get the dose form categories available in the database (see https://doi.org/10.1002/pds.5809) for more details on how routes were classified).

Usage

associatedRouteCategories(x, cdm)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).

Value

A character vector with all available routes.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all dose forms available in a codelist
codelist <- newCodelist(list("codes1" = c(194152L, 1830279L, 40558872L),
                             "codes2" = c(44022939L)))

Get the vocabularies associated with a codelist

Description

Get the vocabularies associated with a codelist

Usage

associatedVocabularies(x, cdm, standardConcept = "Standard", domain = NULL)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.
domain

Character vector with one or more of the OMOP CDM domains. The results will be restricted to the given domains. Check the available ones by running availableDomains(). If NULL, all supported domains are included: Condition, Drug, Procedure, Device, Observation, and Measurement.

Value

Names of available vocabularies.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all vocabularies from a codelist
codelist <- newCodelist(list("codes1" = c(35604877L, 35604394L),
                             "codes2" = c(4214687L)))
associatedVocabularies(cdm = cdm,
                      x = codelist)

Get the names of all available Anatomical Therapeutic Chemical (ATC) classification codes

Description

Get the names of all available Anatomical Therapeutic Chemical (ATC) classification codes

Usage

availableATC(cdm, level = c("ATC 1st"))

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
level

ATC level. Can be one or more of "ATC 1st", "ATC 2nd", "ATC 3rd", "ATC 4th", and "ATC 5th".

Value

A vector containing the names of ATC codes for the chosen level(s) found in the concept table of cdm.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get ATC 1st level classification codes
availableATC(cdm, level = "ATC 1st")

# Get all ATC classification codes
availableATC(cdm, level = c("ATC 1st", "ATC 2nd", "ATC 3rd", "ATC 4th", "ATC 5th"))

Get the available concept classes used in a given set of domains

Description

Get the available concept classes used in a given set of domains

Usage

availableConceptClassIds(cdm, standardConcept = "Standard", domain = NULL)

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.
domain

Character vector with one or more of the OMOP CDM domains. The results will be restricted to the given domains. Check the available ones by running availableDomains(). If NULL, all supported domains are included: Condition, Drug, Procedure, Device, Observation, and Measurement.

Value

The concept classes

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmFromDataset(datasetName = "GiBleed")

# Get all available concept_class_ids in the CDM
availableConceptClassIds(cdm,
                         standardConcept = "Standard")

# Get all available concept_class_ids in the CDM for a specific domain
availableConceptClassIds(cdm,
                         standardConcept = "Standard",
                         domain = "Condition")

# Notice that this corresponds to the information provided by `concept_class_id`
# column in the `concept` table

Get the domains available in the cdm

Description

Get the domains available in the cdm

Usage

availableDomains(cdm, standardConcept = "Standard")

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.

Value

A vector with the domains of the cdm.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all domains available in the CDM for standard concepts
availableDomains(cdm = cdm, standardConcept = "Standard")

Get the dose forms for drug concepts

Description

Get the dose forms for drug concepts

Usage

availableDoseForms(cdm)

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).

Value

The dose forms available for drug concepts.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all domains available in the CDM
availableDoseForms(cdm = cdm)

Get available dose units

Description

Get the available dose units

Usage

availableDoseUnits(cdm, standardConcept = "Standard")

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.

Value

A character vector with available routes.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all dose units available in the CDM
availableDoseUnits(cdm = cdm)

Get the names of all available drug ingredients

Description

Get the names of all available drug ingredients

Usage

availableDrugIngredients(cdm, standardConcept = "Standard")

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.

Value

A vector containing the concept names for all ingredient level codes found in the concept table of cdm.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all drug ingredients available in the CDM for standard concepts
availableDrugIngredients(cdm = cdm)

Get available relationships between concepts

Description

Get available relationships between concepts

Usage

availableRelationshipIds(
  cdm,
  standardConcept1 = "Standard",
  standardConcept2 = "Standard",
  domains1 = "Condition",
  domains2 = "Condition"
)

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept1

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.
standardConcept2

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.
domains1

Character vector with one or more of the OMOP CDM domain. If NULL, all domains are considered.
domains2

Character vector with one or more of the OMOP CDM domain. If NULL, all domains are considered.

Value

A character vector with unique concept relationship values.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all relationship ids in the CDM between `Condition` and `Standard` concepts.
availableRelationshipIds(cdm = cdm,
                         standardConcept1 = "Standard",
                         standardConcept2 = "Standard",
                         domains1 = "Condition",
                         domains2 = "Condition")

Get available drug routes

Description

Get the dose form categories available in the database (see https://doi.org/10.1002/pds.5809) for more details on how routes were classified).

Usage

availableRouteCategories(cdm)

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).

Value

A character vector with all available routes.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all domains available in the CDM
availableRouteCategories(cdm = cdm)

Get the available vocabularies available in the cdm

Description

Get the available vocabularies available in the cdm

Usage

availableVocabularies(cdm, standardConcept = "Standard", domain = NULL)

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
standardConcept

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.
domain

Character vector with one or more of the OMOP CDM domains. The results will be restricted to the given domains. Check the available ones by running availableDomains(). If NULL, all supported domains are included: Condition, Drug, Procedure, Device, Observation, and Measurement.

Value

Names of available vocabularies.

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Get all vocabularies available in the CDM
availableVocabularies(cdm)

# Get all vocabularies available in the CDM for `Standard` and `Condition` concepts
availableVocabularies(cdm,
                      standardConcept = "Standard",
                      domain = "Condition")

Run benchmark of codelistGenerator analyses

Description

Run benchmark of codelistGenerator analyses

Usage

benchmarkCodelistGenerator(cdm)

Arguments

cdm

a CDM reference object

Value

a tibble with time taken for different analysis

Examples

library(CodelistGenerator)

cdm <- mockVocabRef()

timings <- benchmarkCodelistGenerator(cdm)

Get concept ids from JSON files containing cohort definitions

Description

Get concept ids from JSON files containing cohort definitions

Usage

codesFromCohort(path, cdm, type = c("codelist"))

Arguments

path

Path to a file or folder containing JSONs of cohort definitions.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
type

Can be "codelist", "codelist_with_details" or "concept_set_expression".

Value

Named list with concept_ids for each concept set.

Examples

library(CodelistGenerator)
cdm <- mockVocabRef("database")
x <- codesFromCohort(cdm = cdm,
                     path =  system.file(package = "CodelistGenerator",
                     "cohorts_for_mock"))
x
CDMConnector::cdmDisconnect(cdm)

Get concept ids from JSON files containing concept sets [Deprecated]

Description

Get concept ids from JSON files containing concept sets [Deprecated]

Usage

codesFromConceptSet(path, cdm, type = c("codelist"))

Arguments

path

Path to a file or folder containing JSONs of concept sets.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
type

Can be "codelist", "codelist_with_details" or "concept_set_expression".

Value

Named list with concept_ids for each concept set.

Examples

library(CodelistGenerator)
library(omock)

# Create a CDM object
cdm <- mockCdmReference()

# Load JSON files
x <- codesFromConceptSet(cdm = cdm,
                         path =  system.file(package = "CodelistGenerator",
                                             "concepts_for_mock"))
x

# Load JSON files as codelist_with_details
x <- codesFromConceptSet(cdm = cdm,
                         path =  system.file(package = "CodelistGenerator",
                                             "concepts_for_mock"),
                         type = "codelist_with_details")
x

# Load JSON files as concept_set_expression
x <- codesFromConceptSet(cdm = cdm,
                         path =  system.file(package = "CodelistGenerator",
                                             "concepts_for_mock"),
                         type = "concept_set_expression")
x

Compare overlap between two sets of codes

Description

Compare overlap between two sets of codes

Usage

compareCodelists(codelist1, codelist2)

Arguments

codelist1

Output of getCandidateCodes or a codelist
codelist2

Output of getCandidateCodes.

Value

Tibble with information on the overlap of codes in both codelists.

Examples

library(CodelistGenerator)
library(omock)

# Create a CDM object
downloadMockDataset(datasetName = "GiBleed",
                    path = NULL,
                    overwrite = NULL)
cdm <- mockCdmFromDataset(datasetName = "GiBleed")

# Compare two candidate_codes object
codes1 <- getCandidateCodes(
  cdm = cdm,
  keywords = "Arthritis",
  domains = "Condition",
  includeDescendants = TRUE)

codes2 <- getCandidateCodes(
  cdm = cdm,
  keywords = c("osteo"),
  domains = "Condition",
  includeDescendants = TRUE)

compareCodelists(
  codelist1 = codes1,
  codelist2 = codes2)

# Compare two codelists
acetaminophen <- getDrugIngredientCodes(cdm,
                                        name = "acetaminophen",
                                        nameStyle = "{concept_name}",
                                        type = "codelist")

hydrocodone <- getDrugIngredientCodes(cdm,
                                      name = "hydrocodone",
                                      nameStyle = "{concept_name}",
                                      type = "codelist")
compareCodelists(
  codelist1 = acetaminophen,
  codelist2 = hydrocodone)
# Notice that concept_name = NA as `codelist` class does not store this information
# for each concept.

# Compare two codelists_with_details
acetaminophen <- getDrugIngredientCodes(cdm,
                                        name = "acetaminophen",
                                        nameStyle = "{concept_name}",
                                        type = "codelist_with_details")

hydrocodone <- getDrugIngredientCodes(cdm,
                                      name = "hydrocodone",
                                      nameStyle = "{concept_name}",
                                      type = "codelist_with_details")
compareCodelists(
  codelist1 = acetaminophen,
  codelist2 = hydrocodone)

Table showing the route category associated with each dose form.

Description

Table showing the route category associated with each dose form.

Usage

doseFormToRoute

Format

A data frame

dose_form_concept_id

Concept ID of each dose form

dose_form_concept_name

Concept name of each dose form

route_category

Route category associated to the dose form

Examples

library(CodelistGenerator)
doseFormToRoute

Exclude concepts from a codelist

Description

Exclude concepts from a codelist

Usage

excludeConcepts(x, cdm, concepts, codelistName = NULL)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
concepts

Concepts_id to exclude
codelistName

Name or names of codelist in x. If NULL, all codelist present in x will be considered.

Value

A codelist

Examples

library(omock)
library(CDMConnector)

# Creating CDM object
# downloadMockDataset(datasetName = "GiBleed")
cdm <- mockCdmFromDataset(datasetName = "GiBleed")

# Creating codelist
codelist <- getDrugIngredientCodes(cdm,
                                   nameStyle = "{concept_name}")

# Exclude concept to all the codelists:
codelist$acetaminophen
codelist <- codelist |>
  excludeConcepts(cdm, concepts = c(1125315L))
codelist$acetaminophen
# Add a concept to a specific codelist
codelist$amiodarone
codelist <- codelist |>
  excludeConcepts(cdm, concepts = c(1310034L), codelistName = "amiodarone")
codelist$amiodarone

# See function: `addConcepts()` for details on how to add specific concepts
# to a codelist

Get the descendant codes of Anatomical Therapeutic Chemical (ATC) classification codes

Description

Get the descendant codes of Anatomical Therapeutic Chemical (ATC) classification codes

Usage

getATCCodes(
  cdm,
  level = c("ATC 1st"),
  name = NULL,
  nameStyle = "{concept_code}_{concept_name}",
  doseForm = NULL,
  doseUnit = NULL,
  routeCategory = NULL,
  type = "codelist"
)

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
level

ATC level. Can be one or more of "ATC 1st", "ATC 2nd", "ATC 3rd", "ATC 4th", and "ATC 5th".
name

ATC name of interest. For example, c("Dermatologicals", "Nervous System"), would result in a list of length two with the descendant concepts for these two particular ATC groups.
nameStyle

Name style to apply to returned list. Can be one of "{concept_code}","{concept_id}", "{concept_name}", or a combination (i.e., "{concept_code}_{concept_name}").
doseForm

Only codes with the specified dose form will be returned. If NULL, descendant codes will be returned regardless of dose form. Use 'doseForms()' to see the available dose forms.
doseUnit

Only codes with the specified dose unit will be returned. If NULL, descendant codes will be returned regardless of dose unit Use 'availableDoseUnits()' to see the available dose units.
routeCategory

Only codes with the specified route will be returned. If NULL, descendant codes will be returned regardless of route category. Use getRoutes() to find the available route categories.
type

Can be "codelist" or "codelist_with_details".

Value

Concepts with their format based on the type argument

Examples

library(CodelistGenerator)
library(omock)

# Create CDM object
cdm <- mockCdmReference()

# Create a codelist with 1st level ATC codes available in the CDM
codelist <- getATCCodes(cdm = cdm,
                        level = "ATC 1st")
codelist

# Tune the name of the generated codelists
codelist <- getATCCodes(cdm = cdm,
                        level = "ATC 1st",
                        nameStyle = "{concept_name}_{concept_code}")
codelist

# Search for a specific ATC name of interest
codelist <- getATCCodes(cdm = cdm,
                        level = "ATC 2nd",
                        name = "immunostimulants")
codelist

# Restrict concepts to specific dose forms, dose units, or route categories.
# Remember that you can use `availableDoseForm()`, `availableDoseUnit()` and
# `availableRouteCategory()` to explore your codelist.
codelist <- getATCCodes(cdm = cdm,
                        level = "ATC 2nd",
                        doseForm = NULL,
                        doseUnit = NULL,
                        routeCategory = NULL,)
codelist

# You can also create directly a codelist_with_details using the argument `type`
codelist <- getATCCodes(cdm = cdm,
                        level = "ATC 1st",
                        type = "codelist_with_details")
codelist

Perform a systematic search to identify a candidate codelist using the OMOP CDM vocabulary tables.

Description

Based on the given search strategy, this function identifies a set of codes that may represent a clinical event of interest in data mapped to the OMOP CDM. These codes can then be considered for creating a study phenotype.

Usage

getCandidateCodes(
  cdm,
  keywords,
  exclude = NULL,
  domains = "Condition",
  standardConcept = "Standard",
  searchInSynonyms = FALSE,
  searchNonStandard = FALSE,
  includeDescendants = TRUE,
  includeAncestor = FALSE
)

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
keywords

Character vector of terms to search for.

  • The search performed is broad, matching the provided keywords as substrings anywhere within concept names. For example, keywords = c("sep") will find "sepsis", "aseptic necrosis", and "acquired cardiac septal defect" (along with many more).

  • Where more than one word is given, all combinations of those words will be identified. For example, keywords = c("knee osteoarthritis") will identify a concept with the name "osteoarthritis of knee".

  • Multiple keywords can be provided. For example, keywords = c("knee osteoarthritis", "hip osteoarthritis") would identify both "osteoarthritis of knee" and "osteoarthritis of hip"

exclude

Character vector of words to identify concepts to exclude. For example, getCandidateCodes(cdm, keywords = "septic", exclude = "aseptic", domains = "condition") would remove concepts "aseptic" when seaching for concepts with "septic" in their name.

  • When one term contains multiple words (e.g., "knee osteoarthritis"), each word will be search individually, so that "osteoarthritis of knee" would also be excluded. If you only want to exclude partial matching terms, please add "/" at the beginning and the end of each term (e.g., ⁠"/knee osteoarthritis/⁠"). Notice that, with this options, concepts like "rightknee osteoarthritis" will also be excluded (as this is a partial match), but "osteoarthritis of knee" won't be excluded. Different terms can have different rules (e.g., c("hip osteoarthritis", "/knee osteoarthritis/")).

  • With multiple words, if we want exact matches accounting for word boundaries, we need to use ⁠/\b⁠ at the beginning and at the end of each expression. In the previous example, using "/bknee osteoarthritis/\b", "rightknee osteoarthritis" won't be excluded, but "History of knee osteoarthritis" will be excluded.

domains

Character vector with one or more of the OMOP CDM domain for which to search within. If NULL, all domains are included in the search. Use availableDomains(cdm = cdm) to identify available domains to search within.
standardConcept

Character vector with one or more of "Standard", "Classification", and "Non-standard". These correspond to the flags used for the standard_concept field in the concept table of the cdm.
searchInSynonyms

Either TRUE or FALSE. If TRUE the code will also search using both the primary name in the concept table and synonyms from the concept synonym table.
searchNonStandard

Either TRUE or FALSE. If TRUE the code will also search via non-standard concepts.
includeDescendants

Either TRUE or FALSE. If TRUE descendant concepts of identified concepts will be included in the candidate codelist. If FALSE only direct mappings from ICD-10 codes to standard codes will be returned.
includeAncestor

Either TRUE or FALSE. If TRUE the direct ancestor concepts of identified concepts will be included in the candidate codelist.

Value

A "candidate_codes" object. This includes a tibble with the potential codes of interest, along with an attribute containing the search strategy.

Examples

library(CodelistGenerator)
cdm <- mockVocabRef()
getCandidateCodes(
  cdm = cdm,
  keywords = "osteoarthritis"
 )

Get descendant codes for a given concept

Description

Get descendant codes for a given concept

Usage

getDescendants(cdm, conceptId, withAncestor = FALSE)

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
conceptId

concept_id to search
withAncestor

If TRUE, return column with ancestor. In case of multiple ancestors, concepts will be separated by ";".

Value

The descendants of a given concept id.

Examples

library(CodelistGenerator)
cdm <- mockVocabRef()
getDescendants(cdm = cdm, conceptId = 1)

Get descendant codes of drug ingredients

Description

Get descendant codes of drug ingredients

Usage

getDrugIngredientCodes(
  cdm,
  name = NULL,
  nameStyle = "{concept_code}_{concept_name}",
  doseForm = NULL,
  doseUnit = NULL,
  routeCategory = NULL,
  ingredientRange = c(1, Inf),
  type = "codelist"
)

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
name

Names of ingredients of interest. For example, c("acetaminophen", "codeine"), would result in a list of length two with the descendant concepts for these two particular drug ingredients. Users can also specify the concept ID instead of the name (e.g., c(1125315, 42948451)) using a numeric vector.
nameStyle

Name style to apply to returned list. Can be one of "{concept_code}","{concept_id}", "{concept_name}", or a combination (i.e., "{concept_code}_{concept_name}").
doseForm

Only codes with the specified dose form will be returned. If NULL, descendant codes will be returned regardless of dose form. Use 'doseForms()' to see the available dose forms.
doseUnit

Only codes with the specified dose unit will be returned. If NULL, descendant codes will be returned regardless of dose unit Use 'availableDoseUnits()' to see the available dose units.
routeCategory

Only codes with the specified route will be returned. If NULL, descendant codes will be returned regardless of route category. Use getRoutes() to find the available route categories.
ingredientRange

Used to restrict descendant codes to those associated with a specific number of drug ingredients. Must be a vector of length two with the first element the minimum number of ingredients allowed and the second the maximum. A value of c(2, 2) would restrict to only concepts associated with two ingredients.
type

Can be "codelist" or "codelist_with_details".

Value

Concepts with their format based on the type argument.

Examples

library(CodelistGenerator)
cdm <- mockVocabRef()
getDrugIngredientCodes(cdm = cdm,
                       name = "Adalimumab",
                       nameStyle = "{concept_name}")

Show mappings from non-standard vocabularies to standard.

Description

Show mappings from non-standard vocabularies to standard.

Usage

getMappings(
  candidateCodelist,
  cdm = NULL,
  nonStandardVocabularies = c("ATC", "ICD10CM", "ICD10PCS", "ICD9CM", "ICD9Proc",
    "LOINC", "OPCS4", "Read", "RxNorm", "RxNorm Extension", "SNOMED")
)

Arguments

candidateCodelist

Dataframe.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
nonStandardVocabularies

Character vector.

Value

Tibble with the information of potential standard to non-standard mappings for the codelist of interest.

Examples

cdm <- CodelistGenerator::mockVocabRef()
codes <- CodelistGenerator::getCandidateCodes(
  cdm = cdm,
  keywords = "osteoarthritis"
)
CodelistGenerator::getMappings(
  cdm = cdm,
  candidateCodelist = codes,
  nonStandardVocabularies = "READ"
)

Generate a codelist from the intersection of different codelists. The generated codelist will come out in alphabetical order.

Description

Generate a codelist from the intersection of different codelists. The generated codelist will come out in alphabetical order.

Usage

intersectCodelists(x, keepOriginal = FALSE)

Arguments

x

A codelist.
keepOriginal

Whether to keep the original codelist (TRUE) or just return the stratified ones (FALSE).

Value

A codelist

Examples

library(CodelistGenerator)
library(omock)

# Create a CDM object
cdm <- mockCdmReference()

# Intersect two codelists
codelist <- newCodelist(list("mood" = c(37110496L, 4226696L, 4304866L),
                             "manic" = c(37110496L, 4226696L)))

intersectCodelists(codelist, keepOriginal = TRUE)


# Intersect two codelists_with_details
codelist <- asCodelistWithDetails(codelist, cdm)

intersectCodelists(codelist, keepOriginal = FALSE)

Generate example vocabulary database

Description

Generate example vocabulary database

Usage

mockVocabRef(backend = "data_frame")

Arguments

backend

'database' (duckdb) or 'data_frame'.

Value

cdm reference with mock vocabulary.

Examples

library(CodelistGenerator)
cdm <- mockVocabRef()
cdm

Report the search strategy used to identify codes when using the getCandidateCodes() function

Description

Report the search strategy used to identify codes when using the getCandidateCodes() function

Usage

searchStrategy(x)

Arguments

x

A codelist.

Value

A tibble with the search strategy

Examples

library(omock)
library(CodelistGenerator)
library(dplyr, warn.conflicts = FALSE)

# Create CDM object
cdm <- mockCdmFromDataset(datasetName = "GiBleed")
codes <- getCandidateCodes(cdm = cdm,
                           keywords = c("sprain", "fracture"),
                           exclude = "knee",
                           domains = "Condition",
                           standardConcept = "Standard",
                           searchNonStandard = FALSE,
                           searchInSynonyms = TRUE,
                           includeDescendants = TRUE,
                           includeAncestor = FALSE)

searchStrategy(codes) |>
    glimpse()

Stratify a codelist by brand category.

Description

Stratify a codelist by brand category.

Usage

stratifyByBrand(
  x,
  cdm,
  nameStyle = "{codelist_name}_{brand}",
  keepOriginal = FALSE
)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
nameStyle

Naming of the new codelists, use {codelist_name} to include the codelist name and {brand} to include the brand name.
keepOriginal

Whether to keep the original codelist (TRUE) or just return the stratified ones (FALSE).

Value

The codelist with the required stratifications, as different elements of the list.

Examples

library(CodelistGenerator)

cdm <- mockVocabRef()
codes <- newCodelist(list(
  concepts_1 = c(20L, 21L, 22L),
  concepts_2 = c(10L, 13L, 21L)
))

new_codes <- stratifyByBrand(x = codes,
                             cdm = cdm,
                             keepOriginal = TRUE)
new_codes

Stratify a codelist by the concepts included within it.

Description

Stratify a codelist by the concepts included within it.

Usage

stratifyByConcept(
  x,
  cdm,
  nameStyle = "{codelist_name}_{concept}",
  keepOriginal = FALSE
)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
nameStyle

Naming of the new codelists, use {codelist_name} to include the codelist name and {concept} to include the concept name.
keepOriginal

Whether to keep the original codelist (TRUE) or just return the stratified ones (FALSE).

Value

The codelist or a codelist with details with the required stratifications, as different elements of the list.

Examples

library(CodelistGenerator)

cdm <- mockVocabRef()

codes <- newCodelist(list("concepts" = c(20L, 21L)))

new_codes <- stratifyByConcept(x = codes,
                               cdm = cdm,
                               keepOriginal = TRUE)

new_codes

Stratify a codelist by domain category.

Description

Stratify a codelist by domain category.

Usage

stratifyByDomain(
  x,
  cdm,
  nameStyle = "{codelist_name}_{domain}",
  keepOriginal = FALSE
)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
nameStyle

Naming of the new codelists, use {codelist_name} to include the codelist name and {domain} to include the domain name.
keepOriginal

Whether to keep the original codelist (TRUE) or just return the stratified ones (FALSE).

Value

The codelist with the required stratifications, as different elements of the list.

Examples

library(CodelistGenerator)
library(omopgenerics)
cdm <- mockVocabRef()
codes <- newCodelist(list("concepts_1" = c(20L,21L,22L),
                         "concepts_2" = c(10L,13L,21L)))
new_codes <- stratifyByDomain(x = codes,
                             cdm = cdm,
                             keepOriginal = TRUE)
new_codes

Stratify a codelist by dose form.

Description

Stratify a codelist by dose form.

Usage

stratifyByDoseForm(
  x,
  cdm,
  nameStyle = "{codelist_name}_{dose_form}",
  keepOriginal = FALSE
)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
nameStyle

Naming of the new codelists, use {codelist_name} to include the codelist name and {dose_form} to include the dose form name.
keepOriginal

Whether to keep the original codelist (TRUE) or just return the stratified ones (FALSE).

Value

The codelist with the required stratifications, as different elements of the list.

Examples

library(CodelistGenerator)

cdm <- mockVocabRef()

codes <- newCodelist(list("codes" = c(10L, 20L, 21L)))
new_codes <- stratifyByDoseForm(x = codes,
                                cdm = cdm,
                                keepOriginal = TRUE)
new_codes

Stratify a codelist by dose unit.

Description

Stratify a codelist by dose unit.

Usage

stratifyByDoseUnit(
  x,
  cdm,
  nameStyle = "{codelist_name}_{dose_unit}",
  keepOriginal = FALSE
)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
nameStyle

Naming of the new codelists, use {codelist_name} to include the codelist name and {dose_unit} to include the dose unit name.
keepOriginal

Whether to keep the original codelist (TRUE) or just return the stratified ones (FALSE).

Value

The codelist with the required stratifications, as different elements of the list.

Examples

library(CodelistGenerator)

cdm <- mockVocabRef()

codes <- newCodelist(list("concepts" = c(20L, 21L)))
new_codes <- stratifyByDoseUnit(x = codes,
                                cdm = cdm,
                                keepOriginal = TRUE)
new_codes

Stratify a codelist by route category.

Description

Stratify a codelist by route category.

Usage

stratifyByRouteCategory(
  x,
  cdm,
  nameStyle = "{codelist_name}_{route_category}",
  keepOriginal = FALSE
)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
nameStyle

Naming of the new codelists, use {codelist_name} to include the codelist name and {route_category} to include the route category name.
keepOriginal

Whether to keep the original codelist (TRUE) or just return the stratified ones (FALSE).

Value

The codelist with the required stratifications, as different elements of the list.

Examples

library(CodelistGenerator)
library(omopgenerics)
cdm <- mockVocabRef()
codes <- newCodelist(list("concepts" = c(20,21,22)))
new_codes <- stratifyByRouteCategory(x = codes,
                                     cdm = cdm,
                                     keepOriginal = TRUE)
new_codes

Subset a codelist to only those codes from a particular domain.

Description

Subset a codelist to only those codes from a particular domain.

Usage

stratifyByVocabulary(
  x,
  cdm,
  nameStyle = "{codelist_name}_{vocabulary}",
  keepOriginal = FALSE
)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
nameStyle

Naming of the new codelists, use {codelist_name} to include the codelist name and {vocabulary} to include the vocabulary name.
keepOriginal

Whether to keep the original codelist (TRUE) or just return the stratified ones (FALSE).

Value

The codelist with the required stratifications, as different elements of the list.

Examples

library(CodelistGenerator)

cdm <- mockVocabRef()

codes <- stratifyByVocabulary(
  x = newCodelist(list("codes" = c(10L, 13L, 15L))),
  cdm = cdm,
  keepOriginal = TRUE
)

codes

Subset a codelist to only those codes from a particular domain.

Description

Subset a codelist to only those codes from a particular domain.

Usage

subsetOnDomain(x, cdm, domain, negate = FALSE)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
domain

Character vector with one or more of the OMOP CDM domains. The results will be restricted to the given domains. Check the available ones by running availableDomains(). If NULL, all supported domains are included: Condition, Drug, Procedure, Device, Observation, and Measurement.
negate

If FALSE, only concepts with the domain specified will be returned. If TRUE, concepts with the domain specified will be excluded.

Value

The codelist with only those concepts associated with the domain (if negate = FALSE) or the codelist without those concepts associated with the domain (if negate = TRUE).

Examples

library(CodelistGenerator)
library(omopgenerics)
cdm <- mockVocabRef()
codes <- subsetOnDomain(
              x = newCodelist(list("codes" = c(10,13,15))),
              cdm = cdm,
              domain = "Drug")
codes

Subset a codelist to only those codes from a particular domain.

Description

Subset a codelist to only those codes from a particular domain.

Usage

subsetOnDoseForm(x, cdm, doseForm, negate = FALSE)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
doseForm

Dose form/s. See availableDoseForms() to explore available dose forms in your codelist.
negate

If FALSE, only concepts with the dose form specified will be returned. If TRUE, concepts with the dose form specified will be excluded.

Value

The codelist with only those concepts associated with the dose form (if negate = FALSE) or the codelist without those concepts associated with the dose form (if negate = TRUE).

Examples

library(CodelistGenerator)
library(omopgenerics)
cdm <- mockVocabRef()

codelist <- newCodelist(list("codes" = c(10L,20L,21L)))

# Dose forms present in our codelist:
codelist |> associatedDoseForms(cdm)

codes <- subsetOnDoseForm(
              x = codelist,
              cdm = cdm,
              doseForm = "Injection")
codes

codes |> associatedDoseForms(cdm)

Subset a codelist to only those with a particular dose unit.

Description

Subset a codelist to only those with a particular dose unit.

Usage

subsetOnDoseUnit(x, cdm, doseUnit, negate = FALSE)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
doseUnit

Only codes with the specified dose unit will be returned. If NULL, descendant codes will be returned regardless of dose unit Use 'availableDoseUnits()' to see the available dose units.
negate

If FALSE, only concepts with the dose unit specified will be returned. If TRUE, concepts with the dose unit specified will be excluded.

Value

The codelist with only those concepts associated with the dose unit (if negate = FALSE) or codelist without those concepts associated with the dose unit(if negate = TRUE).

Examples

library(CodelistGenerator)
library(omopgenerics)
cdm <- mockVocabRef()
codes <- subsetOnDoseUnit(x = newCodelist(list("codes" = c(20,21))),
                          cdm = cdm,
                          doseUnit = c("milligram"))

codes

Subset a codelist to only those codes with a range of number of ingredients

Description

Subset a codelist to only those codes with a range of number of ingredients

Usage

subsetOnIngredientRange(x, cdm, ingredientRange, negate = FALSE)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
ingredientRange

Used to restrict descendant codes to those associated with a specific number of drug ingredients. Must be a vector of length two with the first element the minimum number of ingredients allowed and the second the maximum. A value of c(2, 2) would restrict to only concepts associated with two ingredients.
negate

If FALSE, only concepts with the ingredient range specified will be returned (both limits included). If TRUE, concepts with number of ingredients outside the range will be returned.

Value

The codelist with only those concepts associated with the domain (if negate = FALSE) or the codelist without those concepts associated with the domain (if negate = TRUE).

Examples

library(CodelistGenerator)
library(omopgenerics)
cdm <- mockVocabRef()
codes <- subsetOnIngredientRange(
              x = newCodelist(list("codes" = c(10L, 13L))),
              cdm = cdm,
              ingredientRange = c(2, 10))
codes

Subset a codelist to only those with a particular route category

Description

Subset a codelist to only those with a particular route category

Usage

subsetOnRouteCategory(x, cdm, routeCategory, negate = FALSE)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
routeCategory

Only codes with the specified route will be returned. If NULL, descendant codes will be returned regardless of route category. Use getRoutes() to find the available route categories.
negate

If FALSE, only concepts with the routeCategory specified will be returned. If TRUE, concepts with the routeCategory specified will be excluded.

Value

The codelist with only those concepts associated with the specified route categories (if negate is FALSE) or the codelist without those concepts associated with the specified route categories (if negate is TRUE).

Examples

library(CodelistGenerator)
library(omopgenerics)
cdm <- mockVocabRef()
codes <- subsetOnRouteCategory(
              x = newCodelist(list("codes" = c(20,21))),
              cdm = cdm,
              routeCategory = "topical")
codes

Subset a codelist to only those codes from a particular vocabulary.

Description

Subset a codelist to only those codes from a particular vocabulary.

Usage

subsetOnVocabulary(x, cdm, vocabulary, negate = FALSE)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
vocabulary

Vocabulary to subset with (i.e., SNOMED)
negate

If FALSE, only concepts with the vocabulary specified will be returned. If TRUE, concepts with the vocabulary specified will be excluded.

Value

The codelist with only those concepts associated with the vocabulary (if negate = FALSE) or the codelist without those concepts associated with the vocabulary (if negate = TRUE).

Examples

library(CodelistGenerator)
library(omopgenerics)
cdm <- mockVocabRef()
codes <- subsetOnVocabulary(
              x = newCodelist(list("codes" = c(1L,13L,15L))),
              cdm = cdm,
              vocabulary = "SNOMED")
codes

Filter a codelist to keep only the codes being used in patient records

Description

Filter a codelist to keep only the codes being used in patient records

Usage

subsetToCodesInUse(
  x,
  cdm,
  minimumCount = 0L,
  table = c("condition_occurrence", "device_exposure", "drug_exposure", "measurement",
    "observation", "procedure_occurrence", "visit_occurrence")
)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
minimumCount

Any codes with a frequency under this will be removed.
table

cdm table of interest.

Value

The filtered codelist with only the codes used in the database

Examples

library(CodelistGenerator)
library(omopgenerics)
cdm <- mockVocabRef("database")
codes <- getCandidateCodes(cdm = cdm,
                           keywords = "arthritis",
                           domains = "Condition",
                           includeDescendants = FALSE)
x <- subsetToCodesInUse(newCodelist(list("cs1" = codes$concept_id,
                               "cs2" = 999)),
                                cdm = cdm)

x
CDMConnector::cdmDisconnect(cdm)

Summarise code use from achilles counts.

Description

Summarise code use from achilles counts.

Usage

summariseAchillesCodeUse(x, cdm, countBy = c("record", "person"))

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
countBy

Either "record" for record-level counts or "person" for person-level counts.

Value

A tibble with summarised counts.

Examples

library(CodelistGenerator)
cdm <- mockVocabRef("database")
oa <- getCandidateCodes(cdm = cdm, keywords = "osteoarthritis")
codelist <- omopgenerics::newCodelist(list(oa = oa$concept_id))
result_achilles <- summariseAchillesCodeUse(codelist, cdm = cdm)
result_achilles
CDMConnector::cdmDisconnect(cdm)

Summarise code use in patient-level data.

Description

Summarise code use in patient-level data.

Usage

summariseCodeUse(
  x,
  cdm,
  countBy = c("record", "person"),
  byConcept = TRUE,
  byYear = FALSE,
  bySex = FALSE,
  ageGroup = NULL,
  dateRange = as.Date(c(NA, NA)),
  useSourceCodes = FALSE
)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
countBy

Either "record" for record-level counts or "person" for person-level counts.
byConcept

TRUE or FALSE. If TRUE code use will be summarised by concept.
byYear

TRUE or FALSE. If TRUE code use will be summarised by year.
bySex

TRUE or FALSE. If TRUE code use will be summarised by sex.
ageGroup

If not NULL, a list of ageGroup vectors of length two.
dateRange

Two dates. The first indicating the earliest cohort start date and the second indicating the latest possible cohort end date. If NULL or the first date is set as missing, the earliest observation_start_date in the observation_period table will be used for the former. If NULL or the second date is set as missing, the latest observation_end_date in the observation_period table will be used for the latter.
useSourceCodes

Whether the codelist provided contains source codes (TRUE) or standard codes (FALSE).

Value

A tibble with count results overall and, if specified, by strata.

Examples

## Not run: 
library(omopgenerics)
library(CodelistGenerator)
con <- DBI::dbConnect(duckdb::duckdb(),
                      dbdir = CDMConnector::eunomiaDir())
cdm <- CDMConnector::cdmFromCon(con,
                                cdmSchema = "main",
                                writeSchema = "main")
acetiminophen <- c(1125315,  1127433, 40229134,
                  40231925, 40162522, 19133768,  1127078)
poliovirus_vaccine <- c(40213160)
cs <- newCodelist(list(acetiminophen = acetiminophen,
                       poliovirus_vaccine = poliovirus_vaccine))
results <- summariseCodeUse(cs,cdm = cdm)
results
CDMConnector::cdmDisconnect(cdm)

## End(Not run)

Summarise code use among a cohort in the cdm reference

Description

Summarise code use among a cohort in the cdm reference

Usage

summariseCohortCodeUse(
  cdm,
  cohortTable,
  x = NULL,
  cohortId = NULL,
  timing = "any",
  countBy = c("record", "person"),
  byConcept = TRUE,
  byYear = FALSE,
  bySex = FALSE,
  ageGroup = NULL,
  useSourceCodes = FALSE
)

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
cohortTable

A cohort table from the cdm reference.
x

A codelist or cohort table name.
cohortId

A vector of cohort IDs to include
timing

When to assess the code use relative cohort dates. This can be "any"(code use any time by individuals in the cohort) or "entry" (code use on individuals' cohort start date).
countBy

Either "record" for record-level counts or "person" for person-level counts.
byConcept

TRUE or FALSE. If TRUE code use will be summarised by concept.
byYear

TRUE or FALSE. If TRUE code use will be summarised by year.
bySex

TRUE or FALSE. If TRUE code use will be summarised by sex.
ageGroup

If not NULL, a list of ageGroup vectors of length two.
useSourceCodes

Whether the codelist provided contains source codes (TRUE) or standard codes (FALSE).

Value

A tibble with results overall and, if specified, by strata

Examples

## Not run: 
library(CodelistGenerator)
library(duckdb)
library(DBI)
library(CDMConnector)
con <- dbConnect(duckdb(),
                 dbdir = eunomiaDir())
cdm <- cdmFromCon(con,
                 cdmSchema = "main",
                 writeSchema = "main")
cdm <- generateConceptCohortSet(cdm = cdm,
                  conceptSet = list(a = 260139,
                                    b = 1127433),
                  name = "cohorts",
                  end = "observation_period_end_date",
                  overwrite = TRUE)

results_cohort_mult <-
summariseCohortCodeUse(omopgenerics::newCodelist(list(cs = c(260139,19133873))),
                      cdm = cdm,
                      cohortTable = "cohorts",
                      timing = "entry")

results_cohort_mult
CDMConnector::cdmDisconnect(cdm)

## End(Not run)

Find orphan codes related to a codelist using achilles counts and, if available, PHOEBE concept recommendations

Description

Find orphan codes related to a codelist using achilles counts and, if available, PHOEBE concept recommendations

Usage

summariseOrphanCodes(
  x,
  cdm,
  domain = c("condition", "device", "drug", "measurement", "observation", "procedure",
    "visit")
)

Arguments

x

A codelist.
cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).
domain

Character vector with one or more of the OMOP CDM domains. The results will be restricted to the given domains. Check the available ones by running availableDomains(). If NULL, all supported domains are included: Condition, Drug, Procedure, Device, Observation, and Measurement.

Value

A summarised result containg the frequency of codes related to (but not in) the codelist.

Examples

library(CodelistGenerator)

cdm <- mockVocabRef("database")
codes <- getCandidateCodes(cdm = cdm,
                          keywords = "Musculoskeletal disorder",
                          domains = "Condition",
                          includeDescendants = FALSE)
codelist <- omopgenerics::newCodelist(list("msk" = codes$concept_id))
orphan_codes <- summariseOrphanCodes(x = codelist,
                                      cdm = cdm)

orphan_codes
CDMConnector::cdmDisconnect(cdm)

Format the result of summariseAchillesCodeUse into a table

Description

Format the result of summariseAchillesCodeUse into a table

Usage

tableAchillesCodeUse(
  result,
  type = "gt",
  header = c("cdm_name", "estimate_name"),
  groupColumn = character(),
  hide = character(),
  style = "default",
  .options = list()
)

Arguments

result

A ⁠<summarised_result>⁠ with results of the type "achilles_code_use".
type

Type of desired formatted table. To see supported formats use visOmopResults::tableType().
header

A vector specifying the elements to include in the header. The order of elements matters, with the first being the topmost header. The header vector can contain one of the following variables: "cdm_name", "codelist_name", "domain_id", "standard_concept_name", "standard_concept_id", "estimate_name", "standard_concept", "vocabulary_id". Alternatively, it can include other names to use as overall header labels.
groupColumn

Variables to use as group labels. Allowed columns are: "cdm_name", "codelist_name", "domain_id", "standard_concept_name", "standard_concept_id", "estimate_name", "standard_concept", "vocabulary_id". These cannot be used in header.
hide

Table columns to exclude, options are: "cdm_name", "codelist_name", "domain_id", "standard_concept_name", "standard_concept_id", "estimate_name", "standard_concept", "vocabulary_id". These cannot be used in header or groupColumn.
style

A character string or custom R code to define the visual formatting of the table. This argument can be provided in two ways: (1) Pre-defined Styles (Character String): Use a name for a built-in style (e.g., "darwin"). See visOmopResults::tableStyle() for available options. (2) Custome Code (Advanced): Supply a block of custom R code. This code must be specific to the table type. See visOmopResults::tableStyleCode() for structural examples.
.options

Named list with additional formatting options. visOmopResults::tableOptions() shows allowed arguments and their default values.

Value

A table with a formatted version of the summariseCohortCodeUse result.

Examples

library(CodelistGenerator)
library(omopgenerics)

cdm <- mockVocabRef("database")
oa <- getCandidateCodes(cdm = cdm, keywords = "osteoarthritis")
result_achilles <- summariseAchillesCodeUse(newCodelist(list(oa = oa$concept_id)),
                                            cdm = cdm)
tableAchillesCodeUse(result_achilles)
CDMConnector::cdmDisconnect(cdm)

Format the result of summariseCodeUse into a table.

Description

Format the result of summariseCodeUse into a table.

Usage

tableCodeUse(
  result,
  type = "gt",
  header = c("cdm_name", "estimate_name"),
  groupColumn = character(),
  hide = c("date_range_start", "date_range_end"),
  style = NULL,
  .options = list()
)

Arguments

result

A ⁠<summarised_result>⁠ with results of the type "code_use".
type

Type of desired formatted table. To see supported formats use visOmopResults::tableType().
header

A vector specifying the elements to include in the header. The order of elements matters, with the first being the topmost header. The header vector can contain one of the following variables: "cdm_name", "codelist_name", "standard_concept_name", "standard_concept_id", "estimate_name", "source_concept_name", "source_concept_id", "domain_id". If results are stratified, "year", "sex", "age_group" can also be used. Alternatively, it can include other names to use as overall header labels.
groupColumn

Variables to use as group labels. Allowed columns are: "cdm_name", "codelist_name", "standard_concept_name", "standard_concept_id", "estimate_name", "source_concept_name", "source_concept_id", "domain_id". If results are stratified, "year", "sex", "age_group" can also be used. These cannot be used in header.
hide

Table columns to exclude, options are: "cdm_name", "codelist_name", "year", "sex", "age_group", "standard_concept_name", "standard_concept_id", "estimate_name", "source_concept_name", "source_concept_id", "domain_id". If results are stratified, "year", "sex", "age_group" can also be used. These cannot be used in header or groupColumn.
style

A character string or custom R code to define the visual formatting of the table. This argument can be provided in two ways: (1) Pre-defined Styles (Character String): Use a name for a built-in style (e.g., "darwin"). See visOmopResults::tableStyle() for available options. (2) Custome Code (Advanced): Supply a block of custom R code. This code must be specific to the table type. See visOmopResults::tableStyleCode() for structural examples.
.options

Named list with additional formatting options. visOmopResults::tableOptions() shows allowed arguments and their default values.

Value

A table with a formatted version of the summariseCodeUse result.

Examples

## Not run: 
library(omopgenerics)
library(CodelistGenerator)
con <- DBI::dbConnect(duckdb::duckdb(),
                      dbdir = CDMConnector::eunomiaDir())
cdm <- CDMConnector::cdmFromCon(con,
                                cdmSchema = "main",
                                writeSchema = "main")
acetiminophen <- c(1125315,  1127433, 40229134,
40231925, 40162522, 19133768,  1127078)
poliovirus_vaccine <- c(40213160)
cs <- list(acetiminophen = acetiminophen,
          poliovirus_vaccine = poliovirus_vaccine)
results <- summariseCodeUse(newCodelist(cs),cdm = cdm)
tableCodeUse(results)
CDMConnector::cdmDisconnect(cdm)

## End(Not run)

Format the result of summariseCohortCodeUse into a table.

Description

Format the result of summariseCohortCodeUse into a table.

Usage

tableCohortCodeUse(
  result,
  type = "gt",
  header = c("cdm_name", "estimate_name"),
  groupColumn = character(),
  hide = c("timing"),
  .options = list(),
  style = NULL
)

Arguments

result

A ⁠<summarised_result>⁠ with results of the type "cohort_code_use".
type

Type of desired formatted table. To see supported formats use visOmopResults::tableType().
header

A vector specifying the elements to include in the header. The order of elements matters, with the first being the topmost header. The header vector can contain one of the following variables: "cdm_name", "codelist_name", "standard_concept_name", "standard_concept_id", "estimate_name", "source_concept_name", "source_concept_id", "domain_id". If results are stratified, "year", "sex", "age_group" can also be used. Alternatively, it can include other names to use as overall header labels.
groupColumn

Variables to use as group labels. Allowed columns are: "cdm_name", "codelist_name", "standard_concept_name", "standard_concept_id", "estimate_name", "source_concept_name", "source_concept_id", "domain_id". If results are stratified, "year", "sex", "age_group" can also be used. These cannot be used in header.
hide

Table columns to exclude, options are: "cdm_name", "codelist_name", "year", "sex", "age_group", "standard_concept_name", "standard_concept_id", "estimate_name", "source_concept_name", "source_concept_id", "domain_id". If results are stratified, "year", "sex", "age_group" can also be used. These cannot be used in header or groupColumn.
.options

Named list with additional formatting options. visOmopResults::tableOptions() shows allowed arguments and their default values.
style

A character string or custom R code to define the visual formatting of the table. This argument can be provided in two ways: (1) Pre-defined Styles (Character String): Use a name for a built-in style (e.g., "darwin"). See visOmopResults::tableStyle() for available options. (2) Custome Code (Advanced): Supply a block of custom R code. This code must be specific to the table type. See visOmopResults::tableStyleCode() for structural examples.

Value

A table with a formatted version of the summariseCohortCodeUse result.

Examples

## Not run: 
con <- DBI::dbConnect(duckdb::duckdb(),
                      dbdir = CDMConnector::eunomiaDir())
cdm <- CDMConnector::cdmFromCon(con,
                                  cdmSchema = "main",
                                  writeSchema = "main")
cdm <- CDMConnector::generateConceptCohortSet(cdm = cdm,
conceptSet = list(a = 260139,
                  b = 1127433),
                  name = "cohorts",
                  end = "observation_period_end_date",
                  overwrite = TRUE)

results_cohort_mult <-
summariseCohortCodeUse(list(cs = c(260139,19133873)),
                      cdm = cdm,
                      cohortTable = "cohorts",
                      timing = "entry")

tableCohortCodeUse(results_cohort_mult)
CDMConnector::cdmDisconnect(cdm)

## End(Not run)

Format the result of summariseOrphanCodes into a table

Description

Format the result of summariseOrphanCodes into a table

Usage

tableOrphanCodes(
  result,
  type = "gt",
  header = c("cdm_name", "estimate_name"),
  groupColumn = character(),
  hide = character(),
  style = NULL,
  .options = list()
)

Arguments

result

A ⁠<summarised_result>⁠ with results of the type "orphan_codes".
type

Type of desired formatted table. To see supported formats use visOmopResults::tableType().
header

A vector specifying the elements to include in the header. The order of elements matters, with the first being the topmost header. The header vector can contain one of the following variables: "cdm_name", "codelist_name", "domain_id", "standard_concept_name", "standard_concept_id", "estimate_name", "standard_concept", "vocabulary_id". Alternatively, it can include other names to use as overall header labels.
groupColumn

Variables to use as group labels. Allowed columns are: "cdm_name", "codelist_name", "domain_id", "standard_concept_name", "standard_concept_id", "estimate_name", "standard_concept", "vocabulary_id". These cannot be used in header.
hide

Table columns to exclude, options are: "cdm_name", "codelist_name", "domain_id", "standard_concept_name", "standard_concept_id", "estimate_name", "standard_concept", "vocabulary_id". These cannot be used in header or groupColumn.
style

A character string or custom R code to define the visual formatting of the table. This argument can be provided in two ways: (1) Pre-defined Styles (Character String): Use a name for a built-in style (e.g., "darwin"). See visOmopResults::tableStyle() for available options. (2) Custome Code (Advanced): Supply a block of custom R code. This code must be specific to the table type. See visOmopResults::tableStyleCode() for structural examples.
.options

Named list with additional formatting options. visOmopResults::tableOptions() shows allowed arguments and their default values.

Value

A table with a formatted version of the summariseOrphanCodes result.

Examples

library(CodelistGenerator)
library(omopgenerics)
cdm <- mockVocabRef("database")
codes <- getCandidateCodes(cdm = cdm,
keywords = "Musculoskeletal disorder",
domains = "Condition",
includeDescendants = FALSE)

orphan_codes <- summariseOrphanCodes(x = newCodelist(list("msk" = codes$concept_id)),
cdm = cdm)

tableOrphanCodes(orphan_codes)

CDMConnector::cdmDisconnect(cdm)

Generate a codelist from the union of different codelists. The generated codelist will come out in alphabetical order.

Description

Generate a codelist from the union of different codelists. The generated codelist will come out in alphabetical order.

Usage

unionCodelists(x, keepOriginal = FALSE)

Arguments

x

A codelist.
keepOriginal

Whether to keep the original codelist (TRUE) or just return the stratified ones (FALSE).

Value

A codelist

Examples

library(CodelistGenerator)
cdm <- mockVocabRef()
getDrugIngredientCodes(cdm,
                        nameStyle = "{concept_name}") |>
unionCodelists()

Get the available version of the vocabulary used in the cdm

Description

Get the available version of the vocabulary used in the cdm

Usage

vocabularyVersion(cdm)

Arguments

cdm

A cdm reference to an OMOP CDM dataset. If data is held within a database, the vocabulary tables should be in the same schema as the clinical tables (person, observation period, and so on).

Value

The vocabulary version being used in the cdm.

Examples

library(CodelistGenerator)
cdm <- mockVocabRef()
vocabularyVersion(cdm = cdm)