# Leveraging quality improvement initiatives to support development of decision support tools in healthcare

## TL;DR

This paper explores how quality improvement projects can help develop healthcare decision tools using modeling and simulation.

## Contribution

It identifies new opportunities and challenges in integrating QI projects with simulation-based decision support tool development.

## Key findings

- QI projects provide access to stakeholders and high-quality patient data for modeling.
- Creating realistic scenarios requires collaboration between QI teams and modelers.
- Upfront investment is needed to align QI goals with modeling efforts effectively.

## Abstract

Modelling and simulation studies have been used to inform the choices and development of quality improvement (QI) initiatives in health care, for example, by helping refine the intervention to be implemented or support decisions around the management of demand and capacity. We do not know whether a modelling study can itself be informed by a QI project and what are the associated benefits and challenges. In this research, we sought to investigate the opportunities and challenges associated with an ongoing health service-led QI project in informing the development of a stochastic simulation-based decision support tool to inform decisions around the commissioning of anticoagulation services for patients with atrial fibrillation. We found that the positive synergies offered by the QI project included good access to stakeholders and envisaged end users, co-producing relevant and impactful scenarios for experimentation, as well as access to good quality individual patient level data. On the other hand, substantial effort was required to populate input parameters with values that pertain to the natural history of the disease and the effectiveness of the different treatments. Our findings indicate that, if stakeholders require modelling results to inform aspects of a QI project, upfront investment is needed to ensure timely interaction between the two studies.