expard

expard constitutes an R package encompassing two primary functionalities:

1. It serves as a simulator for electronic healthcare data, enabling the simulation of extensive patient populations observed across multiple time points. Leveraging R’s functional programming features, the package facilitates the straightforward specification of intricate relationships between drug exposures and adverse drug reactions (ADRs). These relationships may be contingent on various patient attributes such as sex, age, region, among others.

2. The package includes a methodology designed to fit eight exposure models outlined in the associated paper to electronic healthcare data.

Usage

Simulator

The main function of the package is generate_cohort (see ?generate_cohort). For example,

library(expard)

n_drug_ADR_pairs <- 50

generate_cohort(
  n_patients = 100,
  simulation_time = 100,
  n_drug_ADR_pairs = n_drug_ADR_pairs,
  risk_model = rep("risk_model_current_use()", n_drug_ADR_pairs),
  min_chance_drug = rep(0.1, n_drug_ADR_pairs),
  avg_duration = rep(5, n_drug_ADR_pairs),
  max_chance_drug = rep(NULL, n_drug_ADR_pairs),
  prob_guaranteed_exposed = rep(1, n_drug_ADR_pairs),
  min_chance = rep(0.1, n_drug_ADR_pairs),
  max_chance = rep(0.4, n_drug_ADR_pairs),
  verbose = FALSE
)
#> Cohort
#> 
#>   No. patients:      100
#>   No. drug-ADR-pairs:    50
#>   No. time points:   100

simulates a cohort, where

• n_patients is the number of patients simulated in the cohort

• simulation_time is the total number of time steps

• n_drug_ADR_pairs is the number of drug-ADR pairs simulated

• risk_model Vector with risk models. Each risk model is given as a string, e.g., "risk_model_current_use()". The vector must have the length n_drug_ADR_pairs

• min_chance_drug Vector with the probabilities of the drug being prescribed when the drug history and the ADR history have no effect. Must have a length of n_drug_ADR_pairs.

• avg_duration Average number of time points a patient is exposed once exposed to the drug (Determines max_chance) Must have a length of n_drug_ADR_pairs.

• max_chance_drug The probability of the ADR when the drug history and the ADR history have the highest possible effect (Default: NULL) Must have a length of n_drug_ADR_pairs.

• guaranteed_exposed If TRUE, the patient is exposed to the drug at least once Must have a length of n_drug_ADR_pairs.

• min_chance The probability of the ADR when the drug history has no effect Must have a length of n_drug_ADR_pairs.

• max_chance The probability of the ADR when the drug history has the highest possible effect Must have a length of n_drug_ADR_pairs.

Exposure Model Fit

One can fit the eight exposure models by running fit_all_models.R. For more information, see the comments to fit_model.

Acknowledgements

We gratefully acknowledge the financial support from the innovation fund (“Innovationsfonds”) of the Federal Joint Committee in Germany (grant number: 01VSF16020).

Reference

Louis Dijkstra, Tania Schink, Ronja Foraita (2024)
An Exposure Model Framework for Signal Detection based on Electronic Healthcare Data
https://arxiv.org/abs/2404.14213

Louis Dijkstra
Leibniz Institute for Prevention Research & Epidemiology
E-mail: dijkstra (at) leibniz-bips.de