Understanding the complexity of a stroke care system through functional modelling and analysis

Abstract

Stroke is a leading cause of disability and death worldwide. Care of stroke patients is both complex and resource-intensive. Understanding this complexity is crucial for improving healthcare delivery. This study aimed to model and analyze the complexity of a stroke care system. Data were gathered through document review and interviews with 17 healthcare professionals in a city in eastern Canada. The Functional Resonance Analysis Method (FRAM) was employed to model the stroke care system, identify the sources of variability, and propose solutions to improve the stroke care system. The study identified 73 interconnected functions that constitute a functional model of the stroke care system spanning from preadmission to discharge. The functional model illustrates how stroke patients enter the system, receive treatment, and transition after discharge. The results of this study revealed that 1) staffing ratio, 2) health staff training, 3) scheduling, 4) documentation, and 5) equipment and space are significant sources of variability in the stroke care system. These findings enable healthcare professionals to focus on managing significant changes and enhancing their ability to navigate the complexity of the stroke care effectively.

Keywords

• Stroke care system
• Complexity
• Functional modelling
• Functional variability, health care professionals