Summarise an omop table from a cdm object. You will obtain information related to the number of records, number of subjects, whether the records are in observation, number of present domains and number of present concepts.

Usage

summariseClinicalRecords(
  cdm,
  omopTableName,
  recordsPerPerson = c("mean", "sd", "median", "q25", "q75", "min", "max"),
  inObservation = TRUE,
  standardConcept = TRUE,
  sourceVocabulary = TRUE,
  domainId = TRUE,
  typeConcept = TRUE,
  sex = FALSE,
  ageGroup = NULL,
  sample = NULL,
  dateRange = NULL
)

Arguments

cdm: A cdm_reference object.
omopTableName: A character vector of the names of the tables to summarise in the cdm object.
recordsPerPerson: Generates summary statistics for the number of records per person. Set to NULL if no summary statistics are required.
inObservation: Boolean variable. Whether to include the percentage of records in observation.
standardConcept: Boolean variable. Whether to summarise standard concept information.
sourceVocabulary: Boolean variable. Whether to summarise source vocabulary information.
domainId: Boolean variable. Whether to summarise domain id of standard concept id information.
typeConcept: Boolean variable. Whether to summarise type concept id field information.
sex: Boolean variable. Whether to stratify by sex (TRUE) or not (FALSE).
ageGroup: A list of age groups to stratify results by.
sample: An integer to sample the tables to only that number of records. If NULL no sample is done.
dateRange: A list containing the minimum and the maximum dates defining the time range within which the analysis is performed.

Value

A summarised_result object.

Examples

# \donttest{
cdm <- mockOmopSketch()

summarisedResult <- summariseClinicalRecords(
  cdm = cdm,
  omopTableName = "condition_occurrence",
  recordsPerPerson = c("mean", "sd"),
  inObservation = TRUE,
  standardConcept = TRUE,
  sourceVocabulary = TRUE,
  domainId = TRUE,
  typeConcept = TRUE
)
#> ℹ Adding variables of interest to condition_occurrence.
#> ℹ Summarising records per person in condition_occurrence.
#> ℹ Summarising condition_occurrence: `in_observation`, `standard_concept`,
#>   `source_vocabulary`, `domain_id`, and `type_concept`.

summarisedResult
#> # A tibble: 15 × 13
#>    result_id cdm_name       group_name group_level      strata_name strata_level
#>        <int> <chr>          <chr>      <chr>            <chr>       <chr>       
#>  1         1 mockOmopSketch omop_table condition_occur… overall     overall     
#>  2         1 mockOmopSketch omop_table condition_occur… overall     overall     
#>  3         1 mockOmopSketch omop_table condition_occur… overall     overall     
#>  4         1 mockOmopSketch omop_table condition_occur… overall     overall     
#>  5         1 mockOmopSketch omop_table condition_occur… overall     overall     
#>  6         1 mockOmopSketch omop_table condition_occur… overall     overall     
#>  7         1 mockOmopSketch omop_table condition_occur… overall     overall     
#>  8         1 mockOmopSketch omop_table condition_occur… overall     overall     
#>  9         1 mockOmopSketch omop_table condition_occur… overall     overall     
#> 10         1 mockOmopSketch omop_table condition_occur… overall     overall     
#> 11         1 mockOmopSketch omop_table condition_occur… overall     overall     
#> 12         1 mockOmopSketch omop_table condition_occur… overall     overall     
#> 13         1 mockOmopSketch omop_table condition_occur… overall     overall     
#> 14         1 mockOmopSketch omop_table condition_occur… overall     overall     
#> 15         1 mockOmopSketch omop_table condition_occur… overall     overall     
#> # ℹ 7 more variables: variable_name <chr>, variable_level <chr>,
#> #   estimate_name <chr>, estimate_type <chr>, estimate_value <chr>,
#> #   additional_name <chr>, additional_level <chr>

PatientProfiles::mockDisconnect(cdm = cdm)
# }