In this example we will create a candidate codelist for osteoarthritis, exploring how different search strategies may impact our final codelist. First, let’s load the necessary packages and create a cdm reference using mock data.
The mock data has the following hypothetical concepts and relationships:
We will start by creating a codelist with keywords match. Let’s say
that we want to find those codes that contain “Musculoskeletal disorder”
in their concept_name:
getCandidateCodes(
cdm = cdm,
keywords = "Musculoskeletal disorder",
domains = "Condition",
standardConcept = "Standard",
includeDescendants = FALSE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Musculoskeletal disorder",
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = "snomed",
#> standardConcept = "Standard",
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = FALSE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 1 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 1 From initi… Musculoskel… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>Note that we could also identify it based on a partial match or based on all combinations match.
getCandidateCodes(
cdm = cdm,
keywords = "Musculoskeletal",
domains = "Condition",
standardConcept = "Standard",
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeDescendants = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Musculoskeletal",
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = "snomed",
#> standardConcept = "Standard",
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = FALSE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 1 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 1 From initi… Musculoskel… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>
getCandidateCodes(
cdm = cdm,
keywords = "Disorder musculoskeletal",
domains = "Condition",
standardConcept = "Standard",
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeDescendants = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Disorder musculoskeletal",
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = "snomed",
#> standardConcept = "Standard",
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = FALSE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 1 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 1 From initi… Musculoskel… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>Notice that currently we are only looking for concepts with
domain = "Condition". However, we can expand the search to
all domains using domain = NULL.
getCandidateCodes() function will generate a table with
class “candidate_codes”, which contains an attribute with the details of
the search strategy:
candidate_codes <- getCandidateCodes(
cdm = cdm,
keywords = "Musculoskeletal",
domains = "Condition",
standardConcept = "Standard",
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeDescendants = FALSE,
includeAncestor = FALSE
)
searchStrategy(candidate_codes)
#> # A tibble: 13 × 3
#> strategy_id strategy_name strategy_value
#> <int> <chr> <chr>
#> 1 1 package_name "CodelistGenerator"
#> 2 1 package_version "4.1.0"
#> 3 1 function_name "getCandidateCodes"
#> 4 1 cdm "cdm"
#> 5 1 keywords "\"Musculoskeletal\""
#> 6 1 exclude "NULL"
#> 7 1 domains "\"condition\""
#> 8 1 vocabularyId "\"snomed\""
#> 9 1 standardConcept "\"Standard\""
#> 10 1 searchInSynonyms "FALSE"
#> 11 1 searchNonStandard "FALSE"
#> 12 1 includeDescendants "FALSE"
#> 13 1 includeAncestor "FALSE"Now we will include standard and non-standard concepts in our initial
search. By setting
standardConcept = c("Non-standard", "Standard"), we allow
the function to return, in the final candidate codelist, both the
non-standard and standard codes that have been found.
getCandidateCodes(
cdm = cdm,
keywords = "Musculoskeletal disorder",
domains = "Condition",
standardConcept = c("Non-standard", "Standard"),
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeDescendants = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Musculoskeletal disorder",
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = c("icd10", "read", "snomed"),
#> standardConcept = c("Non-standard", "Standard"),
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = FALSE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 2 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 1 From initi… Musculoskel… v5.0 22-JUN-22 Condition SNOMED
#> 2 24 From initi… Other muscu… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>We can also search for multiple keywords simultaneously, capturing all of them with the following search:
getCandidateCodes(
cdm = cdm,
keywords = c(
"Musculoskeletal disorder",
"arthritis"
),
domains = "Condition",
standardConcept = c("Standard"),
includeDescendants = FALSE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = c("Musculoskeletal disorder", "arthritis"),
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = "snomed",
#> standardConcept = "Standard",
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = FALSE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 4 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 1 From initi… Musculoskel… v5.0 22-JUN-22 Condition SNOMED
#> 2 3 From initi… Arthritis v5.0 22-JUN-22 Condition SNOMED
#> 3 4 From initi… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> 4 5 From initi… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>Now we will include the descendants of an identified code using
includeDescendants argument
getCandidateCodes(
cdm = cdm,
keywords = "Musculoskeletal disorder",
domains = "Condition",
standardConcept = "Standard",
includeDescendants = TRUE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Musculoskeletal disorder",
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = "snomed",
#> standardConcept = "Standard",
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = TRUE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 5 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 1 From initi… Musculoskel… v5.0 22-JUN-22 Condition SNOMED
#> 2 2 From desce… Osteoarthro… v5.0 22-JUN-22 Condition SNOMED
#> 3 3 From desce… Arthritis v5.0 22-JUN-22 Condition SNOMED
#> 4 4 From desce… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> 5 5 From desce… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>Notice that now, in the column found_from, we can see
that we have obtain concept_id=1 from an initial search,
and concept_id_=c(2,3,4,5) when searching for descendants
of concept_id 1.
We can also exclude specific keywords using the argument
exclude
getCandidateCodes(
cdm = cdm,
keywords = "Musculoskeletal disorder",
domains = "Condition",
exclude = c("Osteoarthrosis", "knee"),
standardConcept = "Standard",
includeDescendants = TRUE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Musculoskeletal disorder",
#> exclude = c("Osteoarthrosis", "knee"),
#> domains = "condition",
#> vocabularyId = "snomed",
#> standardConcept = "Standard",
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = TRUE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 3 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 1 From initi… Musculoskel… v5.0 22-JUN-22 Condition SNOMED
#> 2 3 From desce… Arthritis v5.0 22-JUN-22 Condition SNOMED
#> 3 5 From desce… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>When multiple words are added within a term (e.g., “knee osteoarthritis”), each word will be searched independently, so that for example, “osteoarthritis of knee” is excluded:
getCandidateCodes(
cdm = cdm,
keywords = "Musculoskeletal disorder",
domains = "Condition",
exclude = c("knee osteoarthritis"),
standardConcept = "Standard",
includeDescendants = TRUE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Musculoskeletal disorder",
#> exclude = "knee osteoarthritis",
#> domains = "condition",
#> vocabularyId = "snomed",
#> standardConcept = "Standard",
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = TRUE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 4 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 1 From initi… Musculoskel… v5.0 22-JUN-22 Condition SNOMED
#> 2 2 From desce… Osteoarthro… v5.0 22-JUN-22 Condition SNOMED
#> 3 3 From desce… Arthritis v5.0 22-JUN-22 Condition SNOMED
#> 4 5 From desce… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>If we only want to exclude exact matching terms (without accounting for words boundaries) we need to add “/” at the beginning and at the end of the term. Hence, using “knee osteoarthritis”, “osteoarthritis of knee” won’t be excluded. However, if we had “right knee osteoarthritis”, it would be excluded.
# No exclusion:
getCandidateCodes(
cdm = cdm,
keywords = "Knee",
domains = "Condition",
exclude = NULL,
standardConcept = c("Standard", "Non-standard"),
includeDescendants = TRUE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Knee",
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = c("icd10", "read", "snomed"),
#> standardConcept = c("Standard", "Non-standard"),
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = TRUE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 2 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 4 From initi… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> 2 8 From initi… Knee osteoa… v5.0 22-JUN-22 Condition Read
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>
# Exclusion looking for terms:
getCandidateCodes(
cdm = cdm,
keywords = "Knee",
domains = "Condition",
exclude = c("knee osteoarthritis"),
standardConcept = c("Standard", "Non-standard"),
includeDescendants = TRUE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Knee",
#> exclude = "knee osteoarthritis",
#> domains = "condition",
#> vocabularyId = c("icd10", "read", "snomed"),
#> standardConcept = c("Standard", "Non-standard"),
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = TRUE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 0 × 13
#> # ℹ 13 variables: concept_id <int>, found_from <chr>, concept_name <chr>,
#> # vocabulary_version <chr>, domain_id <chr>, vocabulary_id <chr>,
#> # concept_class_id <chr>, standard_concept <chr>, concept_code <chr>,
#> # valid_start_date <date>, valid_end_date <date>, invalid_reason <chr>,
#> # found_id <int>
# Exclusion looking for partial matching terms (without word boundaries)
getCandidateCodes(
cdm = cdm,
keywords = "Knee",
domains = "Condition",
exclude = c("/knee osteoarthritis/"),
standardConcept = c("Standard", "Non-standard"),
includeDescendants = TRUE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Knee",
#> exclude = "/knee osteoarthritis/",
#> domains = "condition",
#> vocabularyId = c("icd10", "read", "snomed"),
#> standardConcept = c("Standard", "Non-standard"),
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = TRUE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 1 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 4 From initi… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>
# Exclusion looking for partial matching terms (without word boundaries)
getCandidateCodes(
cdm = cdm,
keywords = "Knee",
domains = "Condition",
exclude = c("/e osteoarthritis/"),
standardConcept = c("Standard", "Non-standard"),
includeDescendants = TRUE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Knee",
#> exclude = "/e osteoarthritis/",
#> domains = "condition",
#> vocabularyId = c("icd10", "read", "snomed"),
#> standardConcept = c("Standard", "Non-standard"),
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = TRUE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 1 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 4 From initi… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>If we want to do exact matching (that means, to find the exact two words “knee osteoarthritis” in the concept name) we need to use “/ at the beginning and at the end of the expression.
getCandidateCodes(
cdm = cdm,
keywords = "Knee",
domains = "Condition",
exclude = c("/\bKnee osteoarthritis/\b"),
standardConcept = c("Standard", "Non-standard"),
includeDescendants = TRUE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Knee",
#> exclude = "/Knee osteoarthritis/",
#> domains = "condition",
#> vocabularyId = c("icd10", "read", "snomed"),
#> standardConcept = c("Standard", "Non-standard"),
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = TRUE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 1 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 4 From initi… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>
# We will now only search for "ee osteoarthritis" to show that
# "knee osteoarthritis" won't be excluded:
getCandidateCodes(
cdm = cdm,
keywords = "Knee",
domains = "Condition",
exclude = c("/\bee osteoarthritis/\b"),
standardConcept = c("Standard", "Non-standard"),
includeDescendants = TRUE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Knee",
#> exclude = "/ee osteoarthritis/",
#> domains = "condition",
#> vocabularyId = c("icd10", "read", "snomed"),
#> standardConcept = c("Standard", "Non-standard"),
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = TRUE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 2 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 4 From initi… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> 2 8 From initi… Knee osteoa… v5.0 22-JUN-22 Condition Read
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>
For example, if we look for
Notice that, for example, if we wanted `keywords = "depression"` and `exclude = "ST depression"`, concepts like "poSTpartum depression" would be excluded. To avoid this,
we could use `exclude = "/ST depression/"`. Notice that, "poST depression" would also be excluded with this option.
Hence, there is another option to exclude exact matching terms accounting for words boundaries: adding "/\b" at the beginning and at the end of the term. For example, if we look for "/\bp osteoarthritis/\b", concepts like "hip osteoarthritis **won't** be excluded.
## Add ancestor
To include the ancestors one level above the identified concepts, we can use the argument `includeAncestor`
<img src="Figures/7.png" alt="" width="100%" />
``` r
codes <- getCandidateCodes(
cdm = cdm,
keywords = "Osteoarthritis of knee",
includeAncestor = TRUE,
domains = "Condition",
standardConcept = "Standard",
includeDescendants = TRUE,
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
)
codes
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Osteoarthritis of knee",
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = "snomed",
#> standardConcept = "Standard",
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = TRUE,
#> includeAncestor = TRUE
#> )
#> # A tibble: 2 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 3 From ances… Arthritis v5.0 22-JUN-22 Condition SNOMED
#> 2 4 From initi… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>We can also pick up codes based on their synonyms. For example,
Osteoarthrosis has a synonym of
Arthritis.
getCandidateCodes(
cdm = cdm,
keywords = "osteoarthrosis",
domains = "Condition",
searchInSynonyms = TRUE,
standardConcept = "Standard",
includeDescendants = FALSE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "osteoarthrosis",
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = "snomed",
#> standardConcept = "Standard",
#> searchInSynonyms = TRUE,
#> searchNonStandard = FALSE,
#> includeDescendants = FALSE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 2 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 2 From initi… Osteoarthro… v5.0 22-JUN-22 Condition SNOMED
#> 2 3 In synonyms Arthritis v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>Notice that if includeDescendants = TRUE,
Arthritis descendants will also be included:
getCandidateCodes(
cdm = cdm,
keywords = "osteoarthrosis",
domains = "Condition",
searchInSynonyms = TRUE,
standardConcept = "Standard",
includeDescendants = TRUE,
searchNonStandard = FALSE,
includeAncestor = FALSE
)
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "osteoarthrosis",
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = "snomed",
#> standardConcept = "Standard",
#> searchInSynonyms = TRUE,
#> searchNonStandard = FALSE,
#> includeDescendants = TRUE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 4 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 2 From initi… Osteoarthro… v5.0 22-JUN-22 Condition SNOMED
#> 2 3 In synonyms Arthritis v5.0 22-JUN-22 Condition SNOMED
#> 3 4 From desce… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> 4 5 From desce… Osteoarthri… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>We can also pick up concepts associated with our keyword via
non-standard search.
codes1 <- getCandidateCodes(
cdm = cdm,
keywords = "Degenerative",
domains = "Condition",
standardConcept = "Standard",
searchNonStandard = TRUE,
includeDescendants = FALSE,
searchInSynonyms = FALSE,
includeAncestor = FALSE
)
codes1
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Degenerative",
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = "snomed",
#> standardConcept = "Standard",
#> searchInSynonyms = FALSE,
#> searchNonStandard = TRUE,
#> includeDescendants = FALSE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 1 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 2 From non-s… Osteoarthro… v5.0 22-JUN-22 Condition SNOMED
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>Let’s take a moment to focus on the standardConcept and
searchNonStandard arguments to clarify the difference
between them. standardConcept specifies whether we want
only standard concepts or also include non-standard concepts in the
final candidate codelist. searchNonStandard determines
whether we want to search for keywords among non-standard concepts.
In the previous example, since we set
standardConcept = "Standard", we retrieved the code for
Osteoarthrosis from the non-standard search. However,
we did not obtain the non-standard code degenerative
arthropathy from the initial search. If we allow non-standard
concepts in the final candidate codelist, we would retireve both
codes:
codes2 <- getCandidateCodes(
cdm = cdm,
keywords = "Degenerative",
domains = "Condition",
standardConcept = c("Non-standard", "Standard"),
searchNonStandard = FALSE,
includeDescendants = FALSE,
searchInSynonyms = FALSE,
includeAncestor = FALSE
)
codes2
#> [1;34mi[0m This is a candidate code searh, see: <link to vignette>
#> [3mCandidate codes[0m generated using [32mCodelistGenerator[0m ([1m4.1.0[0m):
#> getCandidateCodes(
#> cdm = cdm,
#> keywords = "Degenerative",
#> exclude = NULL,
#> domains = "condition",
#> vocabularyId = c("icd10", "read", "snomed"),
#> standardConcept = c("Non-standard", "Standard"),
#> searchInSynonyms = FALSE,
#> searchNonStandard = FALSE,
#> includeDescendants = FALSE,
#> includeAncestor = FALSE
#> )
#> # A tibble: 1 × 12
#> concept_id found_from concept_name vocabulary_version domain_id vocabulary_id
#> * <int> <chr> <chr> <chr> <chr> <chr>
#> 1 7 From initi… Degenerativ… v5.0 22-JUN-22 Condition Read
#> # ℹ 6 more variables: concept_class_id <chr>, standard_concept <chr>,
#> # concept_code <chr>, valid_start_date <date>, valid_end_date <date>,
#> # invalid_reason <chr>