Enabling decision-making and innovation in learning health systems through simulation modelling
Canadian healthcare systems require profound transformations to enhance patient experience, improve population health, reduce costs, and improve the work life of healthcare providers. Learning Health Systems (LHSs) are an approach for undertaking this transformation in an effective, efficient, and sustainable manner with digital technologies as a key enabler for change. However, the successful implementation of a LHS brings with it challenging and potentially risky changes to clinical practices and operations. Simulation modelling is an advanced analytics technique particularly well-suited for informing decision-making and planning prior to and during the transformation of complex systems such as LHSs. Yet, despite the use and demonstrated benefits of simulation modelling in many different industries including healthcare, its application in the context of LHSs has received limited attention. In this article, we discuss how simulation modelling can be leveraged to support better-informed, lower-risk decisions and innovation in LHSs.
Authors
- Antoine Sauré (ORCID: https://orcid.org/0000-0002-0463-7602)
- Lysanne Lessard (ORCID: https://orcid.org/0000-0003-3013-0044)
Institutions
- University of Ottawa (CA)
- Institut du Savoir Montfort (CA)
Publication Details
- Journal
- Healthcare Management Forum
- Published
- 2025-06-12
- DOI
- https://doi.org/10.1177/08404704251348857
- Primary Topic
- Healthcare Operations and Scheduling Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00