OHDSI / PhenotypeR

https://ohdsi.github.io/PhenotypeR/
Apache License 2.0
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PhenotypeR

R-CMD-check Lifecycle:Experimental

The PhenotypeR package helps us to assess the research-readiness of a set of cohorts we have defined. This assessment includes:

Installation

You can install PhenotypeR from GitHub:

# install.packages("remotes")
remotes::install_github("ohdsi/PhenotypeR")

Example usage

library(omopgenerics)
library(CDMConnector)
library(PhenotypeR)
library(CohortConstructor)
library(dplyr)

con <- DBI::dbConnect(duckdb::duckdb(dbdir = CDMConnector::eunomia_dir()))
cdm <- CDMConnector::cdm_from_con(con = con,
                      cdm_schema = "main",
                      write_schema = "main")

cdm$gibleed <- conceptCohort(cdm = cdm,
                                   conceptSet = list(gibleed = 192671L),
                                   name = "gibleed")

result <- cdm$gibleed |>
   phenotypeDiagnostics()
summary(result)
#> A summarised_result object with 18179 rows, 49 different result_id, 1 different
#> cdm names, and 24 settings.
#> CDM names: Synthea synthetic health database.
#> Settings: package_name, package_version, result_type, timing, table_name,
#> cohort_definition_id, cdm_version, vocabulary_version,
#> analysis_outcome_washout, analysis_repeated_events, analysis_interval,
#> analysis_complete_database_intervals, denominator_age_group, denominator_sex,
#> denominator_days_prior_observation, denominator_start_date,
#> denominator_end_date, denominator_target_cohort_name, …, type, and analysis.

Once we have our results we can quickly view them in an interactive application. This shiny app will be saved in a new directory and can be further customised.

shinyDiagnostics(result = result)