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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>These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.