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Diabetes care related process modelling using Process Mining techniques. Lessons learned in the application of

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    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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    Summary

    This study introduces a novel approach for designing diabetes care protocols using Interactive Pattern Recognition. It addresses challenges in creating computer-readable careflows for improved patient self-management and quality of life.

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    Area of Science:

    • Metabolic Disorders
    • Health Informatics
    • Artificial Intelligence in Healthcare

    Background:

    • Diabetes mellitus is a growing metabolic disorder requiring effective self-management, treatment, and lifestyle adjustments for improved patient quality of life.
    • Holistic diabetes care systems leveraging information technology and Evidence-Based Medicine offer continuous patient support.
    • Designing computer-readable careflows for these systems presents significant challenges.

    Purpose of the Study:

    • To propose Interactive Pattern Recognition techniques for the iterative design of diabetes care protocols.
    • To analyze the difficulties encountered when using Process Mining for inferring careflows.
    • To present methods for mitigating the 'Spaghetti Effect' in process mining.

    Main Methods:

    • Application of Interactive Pattern Recognition for iterative protocol design.
    • Analysis of Process Mining techniques for careflow inference.
    • Development of strategies to address the 'Spaghetti Effect' in healthcare process modeling.

    Main Results:

    • Interactive Pattern Recognition facilitates the iterative refinement of diabetes care protocols.
    • Process Mining can lead to complex and unmanageable careflows (Spaghetti Effect).
    • Specific methods are identified to manage and simplify inferred careflows.

    Conclusions:

    • Interactive Pattern Recognition offers an effective method for designing robust diabetes care systems.
    • Addressing the Spaghetti Effect is crucial for the practical implementation of Process Mining in healthcare.
    • Optimized careflows enhance the delivery of continuous and evidence-based diabetes care.