Classifying and Ranking Healthcare Quality Attributes Using Integrated Kano- Fuzzy Analytical Hierarchy Process Model

Abstract

Healthcare is a vital service sector that provides quality treatment services to patients aiming at achieving individual satisfaction. In order to improve the quality of the healthcare sector, patients should be involved in the improvement process. The aim of this study is to provide a systematic approach for determining and prioritizing healthcare quality attributes that affect patients' satisfaction. This is accomplished using an integrated Kano-FAHP model that would provide the basis for better improvement strategies and resource allocation. Based on Kano model principles the collected attributes are analyzed and classified into four main classes: must-be, performance, attractive, and indifferent needs. Statistical tests are performed to ensure the reliability of Kano classification. The classified healthcare quality attributes are structured in hierarchal form, and then prioritized by using FAHP method. Conventional AHP is integrated with fuzzy set theory to capture the uncertainty and ambiguity of patients while concluding judgments. Results indicate that must-be attributes gain the largest weights where "correct information given" and "employee friendless and respectfulness" are the first and second attributes with weights of 0.098 and 0.092, respectively.

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