### Install DrugExposureDiagnostics from CRAN

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Use this command to install the stable version of the package from CRAN.

```r
install.packages("DrugExposureDiagnostics")
```

--------------------------------

### Install DrugExposureDiagnostics Development Version

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Use this command to install the latest development version of the package from GitHub. Requires the 'remotes' package.

```r
install.packages("remotes")
remotes::install_github("darwin-eu/DrugExposureDiagnostics")
```

--------------------------------

### Connect to Mock Database

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Establishes a connection to a mock drug exposure database using the mockDrugExposure() function. This is a simplified setup for demonstration purposes.

```r
# conn <- DBI::dbConnect(
#  RPostgres::Postgres(),
#  dbname = dbname,
#  port = port,
#  host = host,
#  user = user,
#  password = password,
#  bigint = c("numeric")
# )
# cdm <- CDMConnector::cdmFromCon(
#   con = conn,
#   cdmSchema = "cdm schema name"
# )
cdm <- mockDrugExposure()
```

--------------------------------

### Load Required Libraries

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Loads the necessary R libraries for using the DrugExposureDiagnostics package and its dependencies.

```r
library(DrugExposureDiagnostics)
library(CDMConnector)
library(dplyr)
```

--------------------------------

### Accessing Drug Exposure Check Results

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Demonstrates how to access overall and concept-specific drug exposure duration check results from the 'all_checks' object. These results are typically tibbles containing various statistical summaries.

```r
all_checks$drugExposureDurationOverall
#> # A tibble: 1 × 18
#> # Rowwise:  ingredient_concept_id
#>   ingredient_concept_id ingredient    n_records n_sample n_person
#>                   <int> <chr>             <int>    <dbl>    <int>
#> 1               1125315 acetaminophen        44    10000       25
#> # ℹ 13 more variables: n_non_negative_days <int>, n_negative_days <int>,
#> #   proportion_negative_days <dbl>, minimum_drug_exposure_days <dbl>,
#> #   q05_drug_exposure_days <dbl>, q10_drug_exposure_days <dbl>,
#> #   q25_drug_exposure_days <dbl>, median_drug_exposure_days <dbl>,
#> #   q75_drug_exposure_days <dbl>, q90_drug_exposure_days <dbl>,
#> #   q95_drug_exposure_days <dbl>, maximum_drug_exposure_days <dbl>,
#> #   result_obscured <lgl>
all_checks$drugExposureDurationByConcept
#> # A tibble: 6 × 20
#> # Rowwise:  drug_concept_id, drug, ingredient_concept_id
#>   drug_concept_id drug       ingredient_concept_id ingredient n_records n_sample
#>             <int> <chr>                      <int> <chr>          <int>    <dbl>
#> 1         1127078 acetamino…               1125315 acetamino…         8    10000
#> 2         1127433 acetamino…               1125315 acetamino…         8    10000
#> 3        19133768 acetamino…               1125315 acetamino…         8    10000
#> 4        40162522 acetamino…               1125315 acetamino…        12    10000
#> 5        40229134 acetamino…               1125315 acetamino…         6    10000
#> 6        40231925 acetamino…               1125315 acetamino…        NA       NA
#> # ℹ 14 more variables: n_person <int>, n_non_negative_days <int>,
#> #   n_negative_days <int>, proportion_negative_days <dbl>,
#> #   minimum_drug_exposure_days <dbl>, q05_drug_exposure_days <dbl>,
#> #   q10_drug_exposure_days <dbl>, q25_drug_exposure_days <dbl>,
#> #   median_drug_exposure_days <dbl>, q75_drug_exposure_days <dbl>,
#> #   q90_drug_exposure_days <dbl>, q95_drug_exposure_days <dbl>,
#> #   maximum_drug_exposure_days <dbl>, result_obscured <lgl>
```

--------------------------------

### Citation for DrugExposureDiagnostics Package

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

This code displays the recommended citation for the DrugExposureDiagnostics R package, including version and commit information. It also provides a BibTeX entry for LaTeX users.

```r
citation("DrugExposureDiagnostics")
#> To cite package 'DrugExposureDiagnostics' in publications use:>
#> 
#>   Inberg G, Burn E, Burkard T (2026). _DrugExposureDiagnostics:>
#>   Diagnostics for OMOP Common Data Model Drug Records_. R package>
#>   version 1.1.7, commit a2252b98a38603ab7c8342d3a91bd25a13ecf65b,>
#>   <https://github.com/darwin-eu/DrugExposureDiagnostics>.>
#> 
#> A BibTeX entry for LaTeX users is>
#> 
#>   @Manual{,>
#>     title = {DrugExposureDiagnostics: Diagnostics for OMOP Common Data Model Drug Records},>
#>     author = {Ger Inberg and Edward Burn and Theresa Burkard},>
#>     year = {2026},>
#>     note = {R package version 1.1.7, commit a2252b98a38603ab7c8342d3a91bd25a13ecf65b},>
#>     url = {https://github.com/darwin-eu/DrugExposureDiagnostics},>
#>   }
```

--------------------------------

### Write Drug Exposure Check Results to Disk

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Saves the results of drug exposure diagnostics checks to CSV files. Specify the database ID and the output folder where the files should be written.

```r
writeResultToDisk(
  all_checks,
  databaseId = "Synthea",
  outputFolder = tempdir()
)
```

--------------------------------

### Inspect Output Structure

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Displays the names of all the tibbles contained within the output list generated by the executeChecks function. This helps in understanding the structure of the diagnostic results.

```r
names(all_checks)
```

--------------------------------

### Execute All Drug Exposure Checks

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Runs all available diagnostic checks for a specified ingredient (acetaminophen, concept ID 1125315). Ensure the 'bigint' parameter is set correctly when connecting to a real database to avoid merge errors.

```r
all_checks <- executeChecks(
  cdm = cdm,
  ingredients = 1125315,
  checks = c(
    "missing", "exposureDuration", "type", "route", "sourceConcept", "daysSupply",
    "verbatimEndDate", "dose", "sig", "quantity", "diagnosticsSummary"
  )
)
```

--------------------------------

### Summarize Drug Concept Information

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Displays a detailed summary of the conceptSummary tibble, showing all columns and their data types. This is useful for understanding the structure of the drug concept data.

```r
glimpse(all_checks$conceptSummary)
```

--------------------------------

### Select Drug and Concept ID

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Extracts the 'drug_concept_id' and 'drug' columns from the conceptSummary tibble. This snippet is useful for obtaining a concise list of drug concepts and their identifiers.

```r
all_checks$conceptSummary %>%
  select("drug_concept_id", "drug")
```

--------------------------------

### View Missing Values by Drug Concept

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Accesses and displays a tibble summarizing missing values broken down by specific drug concepts. This allows for a more granular analysis of data completeness for individual drugs.

```r
all_checks$missingValuesByConcept
```

--------------------------------

### View Overall Missing Values in Drug Exposures

Source: https://github.com/darwin-eu/drugexposurediagnostics/blob/main/README.md

Accesses and displays a tibble summarizing missing values across all drug exposure records. This is useful for a general overview of data completeness.

```r
all_checks$missingValuesOverall
```

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