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A Big Data-driven Model for the Optimization of Healthcare Processes
Vassiliki Koufi1, Flora Malamateniou1, George Vassilacopoulos1
1Department of Digital Systems, University of Piraeus, Greece.
Healthcare organizations can improve agility and optimize operations using business process management (BPM) and Service-Oriented Architecture (SOA). This framework enables real-time analysis for identifying process improvements.
Area of Science:
- Healthcare Management
- Information Technology in Healthcare
- Business Process Optimization
Background:
- Healthcare organizations operate in a volatile environment driven by technological advancements and evolving business models.
- Agility and responsiveness are crucial for healthcare organizations to excel in this dynamic landscape.
- Optimizing operations requires a focus on healthcare delivery processes and supporting technologies.
Purpose of the Study:
- To present a framework enabling healthcare professionals to gain deeper insights into business processes.
- To facilitate real-time analysis of process-related data for identifying areas of improvement.
- To enhance operational efficiency and responsiveness within healthcare organizations.
Main Methods:
- Leveraging Business Process Management (BPM) for flexible process guidance.
- Utilizing Service-Oriented Architecture (SOA) for a dynamic, cloud-ready infrastructure.
- Implementing business process analytics for extracting actionable insights from data.
Main Results:
- The framework provides enhanced visibility within and across healthcare business processes.
- Real-time analysis reveals specific areas with potential for process enhancement.
- Insights are generated beyond the capabilities of traditional human analysis or IT systems.
Conclusions:
- The proposed framework supports healthcare organizations in achieving greater operational agility.
- Business process analytics, powered by BPM and SOA, is key to uncovering process improvements.
- This approach empowers healthcare professionals with data-driven insights for continuous optimization.
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