A multicriteria decision‐making framework for assessing the performance of gynecobstetrics departments: a case study

Abstract

Gynecobstetrics departments (GDs) oversee diagnosing, monitoring, and treating female reproductive diseases as well as assisting women during pregnancy. Their importance motivates the creation of suitable performance evaluation approaches for identifying weaknesses and designing focused interventions. Therefore, the aim of this paper is twofold: (a) provide an approach for GD performance evaluation and (b) propose interventions tackling the GDs' weaknesses. The fuzzy analytic hierarchy process (FAHP) was first applied to calculate the initial criteria and subcriteria weights under vagueness. Then, the decision-making trial and evaluation laboratory (DEMATEL) was implemented to evaluate interrelations. FAHP and DEMATEL were later combined to estimate the final criteria and subcriteria weights under vagueness and interdependency. Finally, the technique for order of preference by similarity to ideal solution (TOPSIS) was used to rank the GDs and detect improvement opportunities. A case study of a cluster including three GDs is presented to validate the proposed approach. The results evidenced that patient safety and service quality are the most critical aspects in GD performance evaluation. The results from this application can be used by healthcare managers for designing focused interventions targeting improved performance of GDs. This paper fully exploits the advantages of FAHP, DEMATEL, and TOPSIS methods for evaluating performances of GDs. Furthermore, this study presents a novel decision-making model representing the multifactorial context of the GD performance.

Importance Analysis of System Related Fault Based on Improved Decision-Making Trial and Evaluation Laboratory

“…Chen, Jih-Kuang (2021) [6] ISM Determined the threshold by the maximum mean de-entropy method and an additional transitivity check procedure Lopez, DS et al (2021) [7] Rough set theory A systematic evaluation and analysis approach under ambiguity is proposed for evaluating, analyzing, and measuring aspects of internal healthcare performance Li, JS, Xu, KL. (2021) [8] CM Established evaluation index model by identifying relevant hazards of converter steelmaking system You, XL, Hou, FJ (2021) [9] HFLTS Proposed expert weights model based on the similarity and entropy of HFLTSs and introduced the consensus reaching process Ortiz-Barrios, M et al (2021) [10] FAHP Exploited the advantages of FAHP, DEMATEL methods for evaluating performances of GDs Kou, G, et al (2021) [11] fuzzy TOPSIS [14] FCM Help BIM user companies improve their BIM software selection framework and decision-making process during software purchases El-Garaihy, WH (2021) [15] DEA BSC Determined the relationship between the four dimensions of the BSC by identifying supply chain metrics and applying the DEMATEL approach Cui, HY, et al (2021) [16] QFD MOORA Defined green supply chain criteria for each stage of QFD and build IVIF-DEMATEL and IVIF-MOORA hybrid models Hosseini, A, et al (2021) [17] VIKOR Based on Analytical network process of DEMATEL. Using a Hybrid Modified Fuzzy VIKOR Approach to assess and mitigate tourism risks to close the gap Tsuei, HJ, et al (2020) [18] VIKOR Built a decision model of search engine ranking for administrators to improve the performances of websites that satisfy users' needs Li, TC, et al (2020) [19] GRNN Based on the data of my country's marine engineering equipment industry, the grounded theory, and identifying the key influencing factors Pourjavad, E, Shahin, A (2020) [20] AHP TOPSIS Developed by integrating fuzzy DEMATEL, fuzzy hierarchical analysis and by preference order techniques similar to the ideal solution TOPSIS method Chen, TL, et al (2020) [21] VIKOR Help decision makers choose the most appropriate design solution; designers can also improve the gap between product design and expectations Rostamnezhad, M, et al (2020) [22] SD Quantified the importance of the various influencing factors, Considered their complex interactions Titiyal, R, et al (2020) [23] DANP Investigated the relationship between performance levels and performance aspects and calculated their weights Gul, S. (2020) [24] Spherical fuzzy set…”

“…It is impractical to optimize all influential factors, a feasible way is to find out the critical success factors to improve By analyzing the above research status, most of the studies are a fusion of DEMATEL and fuzzy methods, such as fuzzy ANP [23], FAHP [10], fuzzy TOPSIS [11], HELTS [9], Grey [26], etc. But DEMATEL still has two defects: on the one hand, the limitation of their own knowledge and experience or the excessive subjectivity for experts lead to decisionmaking errors, so that the direct influence matrix cannot reflect the real influence relationship.…”

“…Construction of direct relation matrix A direct relation matrix 𝑭𝑭 is constructed according to the fault correlation relationship between components, which 𝑓𝑓 𝑖𝑖𝑖𝑖 indicates the number of times that the component 𝑙𝑙 failure directly leads to the failure of the component 𝑗𝑗, when 𝑙𝑙 = 𝑗𝑗, 𝑓𝑓 𝑖𝑖𝑖𝑖 = 0. As shown in formula (10).…”

Implementation of Vikor Algorithm in Web-Based Recommendation System for Obstetrician Selection

“…The model developed will be used by the system so that it will filter information and adjust it to the criteria entered by the user so that it displays the recommendations that the user wants.Previous research created a decision support system for selecting obstetricians using the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) method [8].In this study, calculations were carried out using five criteria or attributes to determine which obstetrician the pregnant woman would choose. The criteria used are delivery rates, consultation rates, hospital position, obstetrician popularity and experience.…”

Analysis of the cognitive aspects of the preference elicitation process in the compensatory context: a neuroscience experiment with FITradeoff

“…Therefore, a series of methods and various decision support systems (DSSs) have been developed over the years and implemented for the most varied contexts. These seek to provide decision‐makers (DMs) with a structured approach, in order to lead to more rational solutions (Fontana and Morais, 2013; Amaral and Costa, 2014; Stefanakis and Doumpos, 2023; Casas‐Rosal et al., 2023; de Araújo et al., 2021; Nepomuceno et al., 2021; Ortíz‐Barrios et al., 2021; Pintelon et al., 2021). In addition, the decision process can count on the presence of a decision analyst who is responsible for providing methodological support to DMs, by assisting them to construct the decision model and to better understand the process of eliciting preferences (de Almeida et al., 2015).…”