An integrated approach for healthcare services risk assessment and quality enhancement

Abstract

Purpose The purpose of this paper is to introduce an integrated approach using failure modes and effects analysis (FMEA), multiple-criteria decision making (MCDM), mathematical modeling and quality function deployment (QFD) techniques, for risk assessment and service quality enhancement in coronary artery bypass grafting (CABG) as a treatment for cardiovascular diseases (CVDs). Design/methodology/approach First, the disruptions in the CABG process are identified and prioritized following FMEA instructions, using two MCDM techniques, called analytic hierarchy process (AHP) and TOPSIS. Consequently, several corrective activities are identified and weighted on the basis of QFD. Finally, a mathematical model is established to determine the most cost-effective activities for implementation. The approach is developed in a fuzzy environment to reflect the uncertainty and ambiguity of human reasoning. Findings Regarding the CABG process disruption, a total of 30 failure modes in four main categories were identified and prioritized. Moreover, eight corrective activities were devised and ranked according to their impact on the failure modes. Finally, considering a limited amount of budget, a sensitivity analysis on the mathematical model’s objective function indicated that using 30 percent of the total budget, required to implement all corrective activities, was enough to cover more than 70 percent of the effects of corrective activities on the failure modes. Originality/value This paper contributes to the quality risk assessment knowledge by introducing an integrated approach to evaluate and improve healthcare services quality. Also, the case study conducted on the CABG process has not been done by other related studies in the literature.

Adoption of big data analytics practices for sustainability development in the e-commercesupply chain: a mixed-method study

“…Other fuzzy MCDM methods can also be utilized in similar situation. Each method has its own advantages and disadvantages; however, advantages of fuzzy AHP over other MCDM often cited by the studies are its flexibility to incorporate n number of criteria and sub-criteria, ability to ensure consistency in decision-making and ease of application compared to other methods (Mishra, 2021; Pourmadadkar et al. , 2019).…”

Service quality benchmarking of amusement parks using a hybrid approach

“…The literature includes varieties of applications where an integrated AHP-TOPSIS approach had been used for accomplishing similar objectives. Some of them include the ranking of airlines service quality factors (Nejati et al, 2009), risk assessment and quality enhancement in healthcare services (Pourmadadkar et al, 2019), selection of optimum maintenance policy (Hemmati et al, 2019) selection of best mobile phone under fuzzy environment (Singh et al, 2020), etc. Apart from the hybrid methodology of AHP and TOPSIS, other hybrid methodologies also have been implemented by several researchers in similar applications that include network Quality of Service (QoS)-aware service ranking in multi-cloud domain using AHP-PROMETHEE (The Preference Ranking Organization Method for Enrichment of Evaluations) (Bhushan and Pradeep, 2016), benchmarking of service quality in telecommunication services in Kurdistan Region of Iraq using AHP-VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) (Demir, 2019), e-banking website quality assessment using AHP-ELECTRE (ELimination Et Choix Traduisant la REalit e) (Kaya and Kahraman, 2011), service quality assessment of automobiles garages using AHPdigraph (James and James, 2020), assessment of e-service quality of Indian banking industry using AHP-TOPSIS-DEMATEL approach (Decision making trial and evaluation laboratory) (Agrawal et al, 2020), etc.…”

A hybrid multi-criteria decision-making approach to assess the enablers of manufacturing flexibility under fuzzy environment

“…In the first phase, fuzzy AHP method was preferred over other fuzzy MCDM methods like Fuzzy PROMETHEE, Fuzzy VIKOR to determine environment uncertainty criteria and sub-criteria weight due to its flexibility, straightforward calculation, inconsistency measure and intuitive appeal to the decision-makers (Ramanathan, 2001; Pourmadadkar et al , 2019; Kaswan et al , 2019). Also, fuzzy AHP as a standalone tool or fuzzy AHP integrated with other MCDM methods is the most applied fuzzy MCDM technique (Kaya et al , 2019).…”