Days Supply

Run the days supply check

library(DrugExposureDiagnostics)
library(dplyr)
library(DT)

# acetaminophen concept id is 1125315
acetaminophen <- 1125315
cdm <- mockDrugExposure()
acetaminophen_checks <- executeChecks(cdm = cdm, 
                                      ingredients = acetaminophen, 
                                      checks = "daysSupply")

Days supply Overall

This shows the days supply of the drug records summarised on ingredient level.

datatable(acetaminophen_checks$drugDaysSupply,
  rownames = FALSE
)

Column	Description
ingredient_concept_id	Concept ID of ingredient.
ingredient	Name of drug ingredient.
n_records	Number of records for ingredient concept. If n_records is the same as n_sample this means that there are more records but the number was cut at the pre-specified sample number for efficiency reasons.
n_sample	The pre-specified maximum sample. If n_records is smaller than the sample it means that sampling was ignored because the total number of records was already too small.
n_person	Number of individuals.
minimum_drug_exposure_days_supply	Minimum drug exposure days supply
q05_drug_exposure_days_supply_supply	5th quantile of drug exposure days supply
q10_drug_exposure_days_supply	10th quantile of drug exposure days supply
q25_drug_exposure_days_supply	25th quantile of drug exposure days supply
median_drug_exposure_days_supply	Median drug exposure days supply
q75_drug_exposure_days_supply	75th quantile of drug exposure days supply
q90_drug_exposure_days_supply	90th quantile of drug exposure days supply
q95_drug_exposure_days_supply	95th quantile of drug exposure days supply
maximum_drug_exposure_days_supply	Maximum drug exposure days supply
n_different_days_supply_and_drug_dates	Number of records where days supply differs to drug exposure days supply (estimated through drug_exposure_end_date - drug_exposure_start_date + 1). Ideally these two values should overlap because often the drug_exposure_end_date is derived from the days_supply field. However, the days_supply field is not a required field where as drug_exposure_end_date is a required field. If days_supply is missing then it is automatically captured as a difference.
n_days_supply_match_drug_dates	Number of records where days supply is identical to drug exposure days supply (estimated through drug_exposure_end_date - drug_exposure_start_date + 1). Ideally these two values should overlap because often the drug_exposure_end_date is derived from the days_supply field. However, the days_supply field is not a required field where as drug_exposure_end_date is a required field.
n_missing_days_supply	Number of records with missing days supply. This field together with n_different_days_supply_and_drug_dates and n_days_supply_match_drug_dates shall be identical to n_records.
proportion_different_days_supply_and_drug_dates	Proportion of records where days supply differs to drug exposure days supply (estimated through drug_exposure_end_date - drug_exposure_start_date + 1).
proportion_days_supply_match_drug_dates	Proportion of records where days supply is idential to drug exposure days supply (estimated through drug_exposure_end_date - drug_exposure_start_date + 1).
proportion_missing_days_supply
result_obscured	TRUE if count has been suppressed due to being below the minimum cell count, otherwise FALSE.

Days supply by drug concept

This shows the days supply on the drug concept level. The tables are identical to the overall just including two more columns at the beginning.

Column	Description
drug_concept_id	ID of the drug concept.
drug	Name of the drug concept.

datatable(acetaminophen_checks$drugDaysSupplyByConcept,
  rownames = FALSE
)