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Shaping the future design of paramedicine: A knowledge to action framework to support paramedic system modernization
Timothy Makrides1, Madelyn P Law2, Linda Ross3
1Department of Paramedicine, School of Primary and Allied Health Care, Faculty of Medicine, Nursing & Health Science, Monash University, Clayton, Australia; British Columbia Emergency Health Services, Vancouver, Canada.
Background:
Over the past two decades, the demands placed on modern paramedic systems has changed. Paramedic services can no longer continue to operate on a traditional response model where more ambulances are deployed to meet the rising demand of patients calling for their health needs. Recent research has explored system design in paramedicine and its relationship with organizational performance. Two subsequent paramedic systems have been identified with one, the Professionally Autonomous paramedic system, being linked to higher performance. Yet, how to operationalize this model for system modernization continues to be a gap in practice.
Objective:
To provide health leaders and policy makers with a framework from which to drive paramedic system modernization.
Methods:
This study uses the Knowledge to Action framework to develop an implementation plan for systems that seek to modernize their service delivery model toward that of a Professionally Autonomous paramedic system.
Results:
A detailed plan of the steps required to undertake system transformation are outlined. Whilst this framework outlines the components required for system modernization, it does not propose an in-depth outline of each of the steps required to achieve each component. Rather, end users are encouraged to develop individual implementation plans tailored to the local context using the comprehensive tools outlined within.
Conclusion:
This knowledge to action framework provides health leaders and policy makers with a uniform roadmap for paramedic system modernization intended to improve health (clinical) outcomes as well as health system outcomes through the Professional Autonomous paramedicine model.
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