A Multi-Granularity Triangular Fuzzy Approach for Diabetes Blood Glucometer Selection Using PROMETHEE and Three-Way Decision

Problem Background

The advancement of modern medical technology has significantly improved the ability of diabetes patients to manage and monitor their blood glucose levels (Domingo-Lopez, 2022). Glucometers, being convenient medical devices, are extensively utilized in both home and clinical environments. Nonetheless, the market is saturated with a wide array of glucometer models and brands, which presents a challenge for patients in selecting the most suitable one. Factors such as accuracy, quality, after-sales support, and pain sensation must be taken into consideration. Patients must carefully evaluate these factors to choose a glucometer that aligns with their specific needs and preferences. Consequently, in order to aid patients in making well-informed decisions, it is essential to thoroughly comprehend the challenges associated with selecting a glucometer and provide corresponding solutions. Such research endeavors contribute to enhancing the effectiveness of diabetes management, improving patients' quality of life, and guiding medical device manufacturers in meeting the needs and expectations of patients, thus fostering product improvement and innovation.

When selecting a glucometer, patients must take into account various factors, including price, accuracy, and convenience. However, these factors introduce a level of ambiguity and uncertainty that complicates the decision-making process. In order to tackle these challenges, this study presents a comprehensive model that integrates triangular fuzzy sets (TFSs), the TWD, and the PROMETHEE multi-attribute decision-making method to improve the efficiency and accuracy of selecting glucometers.