Missingness

In DrugExposureDiagnostics: Diagnostics for OMOP Common Data Model Drug Records

options(rmarkdown.html_vignette.check_title = FALSE)
knitr::opts_chunk$set(
  warning = FALSE,
  message = FALSE,
  collapse = TRUE,
  comment = "#>"
)

Run missingness check

library(DrugExposureDiagnostics)
cdm <- mockDrugExposure()
result <- executeChecks(
  cdm = cdm,
  checks = "missing"
)

Overall missingness

This shows the missingness of the drug records summarised on ingredient level.

DT::datatable(result$missingValuesOverall,
  rownames = FALSE
)

| Column | Description | :------------- | :------------- | ingredient_concept_id | Concept ID of ingredient. | ingredient | Name of drug ingredient. | variable | the variable for which missingness was assessed. | 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_records_not_missing_value | The number of records for which there is no missingness in the variable of interest. | n_records_missing_value | The number of records with missing values for the variable of interest. | proportion_records_missing_value | The proportion of records with missing values for the variable of interest. | result_obscured | TRUE if count has been suppressed due to being below the minimum cell count, otherwise FALSE. |

Missingness by drug concept

This shows the missingness on drug concept level.

DT::datatable(result$missingValuesByConcept, rownames = FALSE)

| Column | Description | :------------- | :------------- | drug_concept_id | ID of the drug concept. | drug | Name of the drug concept. | ingredient_concept_id | Concept ID of ingredient. | ingredient | Name of drug ingredient. | variable | the variable for which missingness was assessed. | n_records | Number of records for drug 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_records_not_missing_value | The number of records for which there is no missingness in the variable of interest. | n_records_missing_value | The number of records with missing values for the variable of interest. | proportion_records_missing_value | The proportion of records with missing values for the variable of interest. | result_obscured | TRUE if count has been suppressed due to being below the minimum cell count, otherwise FALSE. |

DrugExposureDiagnostics documentation built on Sept. 16, 2025, 9:11 a.m.