Application of fuzzy TOPSIS for prioritization of patients on elective surgeries waiting list - A novel multi-criteria decision-making approach

Abstract

Prioritizing patients is a growing concern in healthcare. Once resources are limited, prioritization is considered an effective and viable solution in provision of healthcare treatment to awaiting patients. Prioritization is a preferred approach that helps clinicians to apportion scarce resources fairly and transparently. In this study, a novel methodology of prioritizing the patient is formulated using fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The objective is based on actual hospital conditions in Pakistan. The proposed methodology has two contributions: objective scoring mechanism that translates the patient’s condition given in human linguistic terms; and second methodology to prioritize patients according to corresponding scores. To validate the proposed methodology, simulation was carried out on actual data collected in real-time by surgeons, while providing consultations to their patients. The proposed methodology outperforms the traditional methodology by reducing average waiting time by 34% (from 4.246 to 2.810 days), minimize wait time and delays by 46.7% (from 15 to 8 days), and number of surgery days by 18%. The majority of the previously presented researched methodologies prioritize the patients subjectively. This study presents an objective methodology to prioritize the patients and decrease wait-times while ensuring transparency and equity.

Sistem Pendukung Keputusan Kinerja Karyawan Terbaik Dengan Menggunakan Kombinasi Metode TOPSIS Dan Metode ROC

“…TOPSIS adalah metode pengambilan keputusan multikriteria dengan prinsip harus mempunyai jarak terdekat dari solusi ideal positif dan jarak terpanjang dari ideal negatif untuk menentukan kedekatan relatif dengan solusi optimal [1], [6] . Solusi ideal positif yaitu sebagai jumlah dari seluruh nilai terbaik yang dapat dicapai untuk setiap atribut, sedangkan solusi ideal negatif terdiri dari seluruh nilai terburuk yang dicapai untuk setiap atribut [7], [8]. Adapun tahapan-tahap metode TOPSIS sebagai berikut [9], [10] :…”

A new distance between rankings

“…The usage of a new metric is not limited only to measurements between different rankings. Such distance can also power distance-based methods such as TOPSIS [24] to potentially improve the decision-making quality. Additionally, it can be used in other domains besides MCDA, for example, in machine-learning-related algorithms that utilize distance functions, such as clustering [11] , [13] , fuzzy clustering [12] or classification [30] , where newly developed distances can greatly improve existing algorithms.…”

A Novel Trigonometric Entropy Measure Based on the Complex Proportional Assessment Technique for Pythagorean Fuzzy Sets

“…To this end, fuzzy sets (FS) were introduced by Zadeh [14] so that decision makers can include uncertainty through the use of a membership function and express its degree of membership and non-membership. A number of examples using fuzzy approaches to solve multicriteria problems have been developed, such as the use of fuzzy technique for order of preference by similarity to ideal solution (TOPSIS) prioritization of patients on elective surgery waiting lists, presented by Rana et al [15].…”