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.
getCandidateCodes(
cdm,
keywords,
exclude = NULL,
domains = "Condition",
standardConcept = "Standard",
searchInSynonyms = FALSE,
searchNonStandard = FALSE,
includeDescendants = TRUE,
includeAncestor = FALSE
)A "candidate_codes" object. This includes a tibble with the potential codes of interest, along with an attribute containing the search strategy.
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).
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"
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.
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.
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.
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.
Either TRUE or FALSE. If TRUE the code will also search via non-standard concepts.
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.
Either TRUE or FALSE. If TRUE the direct ancestor concepts of identified concepts will be included in the candidate codelist.
# \donttest{
library(CodelistGenerator)
cdm <- mockVocabRef()
getCandidateCodes(
cdm = cdm,
keywords = "osteoarthritis"
)
# }
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