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Multicriteria Risk Evaluation Model: Utilizing Fuzzy Logic for Improved Transparency and Quality of Risk Evaluation

Rok Drnovšek1,2, Marija Milavec Kapun3, Simona Šteblaj1

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Summary

A new multicriteria decision-making and fuzzy logic model improves healthcare risk evaluation, offering greater transparency and handling uncertainty better than traditional risk matrices.

Keywords:
DEXdecision supportfuzzy logicmulti-criteria decision-makingpatient carerisk management

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Area of Science:

  • Healthcare Management
  • Decision Science
  • Risk Analysis

Background:

  • Risk management is crucial for healthcare quality assurance.
  • Traditional risk matrices have limitations in evaluating healthcare risks.
  • A novel approach is needed to enhance risk evaluation transparency and quality.

Purpose of the Study:

  • Introduce a novel risk evaluation model for healthcare.
  • Utilize multicriteria decision-making and fuzzy logic for enhanced risk assessment.
  • Improve transparency and quality in healthcare risk evaluation processes.

Main Methods:

  • Developed a Multicriteria Evaluation Model using Decision Expert and expert knowledge.
  • Integrated fuzzy logic with partial degrees of membership and probabilistic analysis.
  • Tested the model with healthcare professionals and compared it to the traditional risk matrix.

Main Results:

  • The model incorporates multicriteria decision-making within the risk matrix framework for better user understanding.
  • Evaluations using the new model were similar or marginally higher than the risk matrix.
  • Fuzzy logic's degrees of membership allowed for nuanced articulation of risk consequences, unlike traditional methods.

Conclusions:

  • The novel model enhances decision-making transparency and in-depth analysis of risk evaluation.
  • Degrees of membership highlighted diverse uncertainty handling strategies, exposing weaknesses of single-value approaches.
  • This approach can be applied beyond healthcare to improve risk evaluation in various settings.