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Outcome centred process mapping in healthcare using random forest and process mining.

Simone Leonetti1, Chiara Seghieri2, Domenico Tricò3

  • 1Management and Healthcare Laboratory, Interdisciplinary Research Center "Health Science", Sant Anna School of advanced studies, Piazza Martiri della Libertà 33, Pisa, 56127, Italy. s.leonetti@santannapisa.it.

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Summary
This summary is machine-generated.

This study introduces a novel approach combining process mining and random forest to map patient flow, focusing on outcomes. This method identifies complex patient groups needing tailored strategies, improving healthcare efficiency and patient care.

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Area of Science:

  • Healthcare Management
  • Process Mining
  • Data Science

Background:

  • System process mapping is crucial for managing complex healthcare systems and improving patient flow.
  • Traditional methods offer limited insights by only comparing pathways, neglecting outcomes and attributes.
  • Healthcare process mining presents challenges due to specialized knowledge requirements and process variability.

Purpose of the Study:

  • To develop an outcome-centered process mapping approach for healthcare systems.
  • To integrate process mining discovery with random forest for enhanced system analysis.
  • To analyze complex patient pathways and identify factors influencing treatment challenges.

Main Methods:

  • A combined stepwise approach using random forest (RF) and process mining (PM) discovery.
  • Analysis of the MIMIC-IV v2.2 dataset, encompassing diverse hospital data from 2008-2019.
  • Focus on patient flow, including emergency department (ED), measurements, procedures, and intensive care unit (ICU) transfers.

Main Results:

  • Older patients with high ED priority and multimorbidity represent complex cases requiring specialized management.
  • The proposed method effectively maps processes from a data-driven, outcome-centered perspective.
  • Identified patient characteristics associated with complex treatment pathways.

Conclusions:

  • The combined RF and PM approach enables comprehensive, outcome-centered process mapping.
  • Tailored management strategies are essential for complex patient groups, aligning with clinical practice.
  • Potential applications include real-time prediction of length of stay to optimize resources and care quality.