Health systems are under pressure to deliver high quality care to improve outcomes, access and financial sustainability. In the past decade, Ontario pursued such improvements through a series of transformation initiatives aimed at moving care provision to the community settings and integrating care around patient pathways through system. In this dissertation we present operational research (OR) approaches to facilitate whole-system strategic planning for health systems, with a focus on patient flow among care sectors to address transformation challenges in Ontarioâ s health care system and its regional health authorities.
Firstly, we expand on Soft OR methods to collaboratively develop a qualitative model to capture the boundary and transitional view of patient flows across major care sectors in a health region. The model is not scoped around a specific question, but is meant to be a broad platform for exploring the patient flow relationships among multiple care domains.
Secondly, we build on the findings of the qualitative model, and leverage the administrative datasets across these major care sectors to develop a high fidelity simulation model to evaluate the effects of policy interventions and their effects on system-wide patient flows. Methodologically this simulation builds on the structural simplicity of system dynamics with comprehensive, patient-level data to achieve a highly flexible simulation to model flows for a broad and modifiable range of patient cohorts and interventions.
Finally, we implement both models in the analysis of whole-system care policies. The qualitative model is used for the analysis of slow stream rehabilitation policy options and is utilized to identify conflicts of this initiative with existing patient flow interventions. The simulation model is used to assess the cross-sector patient flow impacts of implementing stroke best practices. The results highlight the importance of community care investments and cross-sector referral patterns in realizing the greatest benefits from this policy.Ph.D
