Development of an Intuitive GUI-Based Fuzzy Multi-Criteria Decision Model for Comprehensive Hospital Service Quality Evaluation and Indexing

Abstract

Recently, hospital care and other services have become increasingly important for patient satisfaction. Better hospital care and assistance improve patients’ medical conditions, management trust, and financial success. In this regard, monitoring and measuring hospital service quality is necessary to improve patient satisfaction and wellness. However, the evaluation of healthcare service quality is a complex and critical task due to its intangible nature. Existing methodologies often struggle to effectively incorporate multiple criteria and address uncertainties inherent in healthcare evaluations. To address these challenges, this research work seeks to develop a comprehensive and robust approach for evaluating hospital service quality to improve decision making and resource allocation for service enhancement. This study aims to evaluate multi-faceted healthcare service quality by combining many criteria and uncertainties into a single index. The model is constructed methodically utilizing fuzzy logic and decision modeling. A dataset collected from diverse healthcare facilities covering various medical specialties and regions is employed to validate and refine the model. Numerous criteria, factors, and dimensions are examined and embedded into the development of the model. Fuzzy logic is used to capture and manage healthcare evaluations’ inherent vagueness and imprecision, yielding more accurate and comprehensive outcomes. The model’s outcome is the hospital service quality fuzzy index (HSQFI), an easy-to-understand single performance measure. A graphical user interface (GUI) is developed for collecting data, and then it shows the results in the form of barriers and recommendations. Based on the findings, recommendations in terms of barriers (service criteria) to enhance the hospital’s service quality have been made. This approach can be a tool for managers or other stakeholders to quickly realize the success of their service plans and pinpoint areas that may need improvement in the future.