Adaptive healthcare processes for personalized emergency clinical pathways

Area of Science:

• Emergency medicine
• Health informatics
• Artificial intelligence in healthcare

Background:

• Effective emergency care requires coordination between pre-hospital and in-hospital services.
• Current emergency care delivery can be enhanced through personalized clinical pathways.
• Optimizing resource allocation is crucial for efficient emergency healthcare.

Purpose of the Study:

• To propose a framework for personalized emergency clinical pathways.
• To leverage Business Process Management Systems (BPMS) and semantic technologies for dynamic pathway generation.
• To improve emergency healthcare delivery through context-aware process modeling.

Main Methods:

• Utilizing ontologies to model emergency case history, resource availability, and clinical guidelines.
• Integrating clinical guideline logic into emergency healthcare processes at run-time.
• Employing semantic technologies and BPMS for adaptive process management.

Main Results:

• The proposed framework enables the creation of context-specific emergency care plans.
• It facilitates better resource utilization by aligning pathways with available assets.
• Inferred process models are tailored to individual emergency case needs and guidelines.

Conclusions:

• A novel framework integrating ontologies and BPMS can support personalized emergency clinical pathways.
• This approach enhances emergency healthcare by dynamically adapting processes to real-time information.
• The system promotes efficient resource management and adherence to clinical guidelines.