# On simulation reuse in healthcare applications

## TL;DR

This paper explores how reusing simulation models can make healthcare operations research more practical and widely adopted.

## Contribution

The paper introduces a triadic framework for model reuse in healthcare simulations, highlighting three complementary modes.

## Key findings

- Three modes of model reuse were identified: FAIR/open-science aspects, reusable conceptual domains, and black-box reuse.
- These modes are shown to complement and enhance each other in healthcare simulation contexts.
- Concrete mechanisms and tools for integrating these modes are proposed to boost simulation adoption in healthcare.

## Abstract

Simulation remains a promising technology in healthcare operations research and process optimisation. However, while there have been many research projects applying simulation in this context, the level of sustained uptake in healthcare practice has been lower. We conjecture that an important reason for this is the time, cost and complexity of developing simulation models. Therefore, being able to reuse models would be key to improving uptake of simulation in healthcare. Conventional practice is that simulation models are developed from scratch for every new problem. In this paper, we review current strategies for model reuse in the healthcare context, aiming to identify complementary techniques for model reuse available to healthcare modellers and managers. Specifically, we identify three different modes of model reuse – forming a triadic framework – each prioritising a different aspect: FAIR and open-science aspects of model reuse; reusable conceptual simulation domains through modelling languages and transformations; and black-box model(-component) reuse including distributed simulation. We show how these three perspectives complement and enhance each other. We believe that developing concrete mechanisms and tools for leveraging the relationships between the three different modes of model reuse will be key to increasing the uptake of simulation modelling in healthcare practice.