options(rmarkdown.html_vignette.check_title = FALSE) knitr::opts_chunk$set( warning = FALSE, message = FALSE, collapse = TRUE, comment = "#>" )
library(DrugExposureDiagnostics) cdm <- mockDrugExposure() result <- executeChecks( cdm = cdm, checks = "sig" )
This shows the sig(netur) of the drug records summarised on ingredient level. The signetur of a prescription contains the information of when, how often, and how much of a drug a patient shall use.
DT::datatable(result$drugSig, rownames = FALSE )
| Column | Description |
:------------- | :------------- |
ingredient_concept_id | Concept ID of ingredient. |
ingredient | Name of drug ingredient. |
sig | The signetur of a prescription. The sig is usually only available for prescription and often contains free text or only semi-standardised information. |
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. |
result_obscured | TRUE if count has been suppressed due to being below the minimum cell count, otherwise FALSE. |
This shows the sig(netur) on the drug concept level. The signetur of a prescription contains the information of when, how often, and how much of a drug a patient shall use. 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. |
DT::datatable(result$drugSigByConcept, rownames = FALSE)
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