# Health economic simulation modeling

## Overview

`hesim`

is a modular and computationally efficient R package for health
economic simulation modeling and decision analysis that provides a
general framework for integrating statistical analyses with economic
evaluation. The package supports cohort discrete time state transition
models (DTSTMs), N-state partitioned survival models (PSMs), and
individual-level continuous time state transition models (CTSTMs),
encompassing both Markov (time-homogeneous and time-inhomogeneous) and
semi-Markov processes. It heavily utilizes `Rcpp`

and `data.table`

,
making individual-level simulation, probabilistic sensitivity analysis
(PSA), and incorporation of patient heterogeneity fast.

Features of the current version can be summarized as follows:

- Cohort DTSTMs, individual-level CTSTMs, and N-state PSMs that encompass Markov and semi-Markov processes
- Options to build models directly from fitted statistical models or by defining them in terms of expressions
- Parameter estimates from either an
`R`

based model or from an external source - Convenience functions for sampling model parameters from parametric distributions or via bootstrapping
- Parameter uncertainty propagated with PSA
- Modeling patient heterogeneity
- Performing cost-effectiveness analyses and representing decision uncertainty from PSAs
- Simulation code written in
`C++`

to boost performance

## Installation

You can install the current release from CRAN or the most up to date development version from GitHub.

```
# Install from CRAN:
install.packages("hesim")
# Install the development version from GitHub:
# install.packages("devtools")
devtools::install_github("hesim-dev/hesim")
```

## Getting started

There are two good places to start:

The Introduction to

`hesim`

article provides a quick introduction.Our preprint describes the package (including mathematical details) more thoroughly.

You might also want to explore our example analyses which can be found in the preprint and web articles. They are summarized in the table below, with some drawn from the Decision Modeling for Health Economic Evaluation textbook. Key areas of focus are the (i) statistical models of disease progression (in terms of the baseline risk and relative treatment effects) and (ii) the available data (either individual patient data (IPD) or aggregate-level data).

Baseline risk

Treatment effect

## Citing hesim

If you use `hesim`

, please cite as follows:

```
Devin Incerti and Jeroen P Jansen (2021). hesim: Health Economic
Simulation Modeling and Decision Analysis. arXiv:2102.09437
[stat.AP], URL https://arxiv.org/abs/2102.09437.
A BibTeX entry for LaTeX users is
@Misc{incerti2021hesim,
author = {Devin Incerti and Jeroen P. Jansen},
title = {hesim: Health Economic Simulation Modeling and Decision Analysis},
year = {2021},
eprint = {2102.09437},
archiveprefix = {arXiv},
primaryclass = {stat.AP},
url = {https://arxiv.org/abs/2102.09437},
}
```