Satisfaction-based patient classification: Improving the quality of healthcare services

Abstract

ABSTRACT Patient satisfaction is crucial for evaluating healthcare quality. However, its potential as a patient classification strategy remains to be explored, leaving healthcare institutions without clear guidance in this regard. This study introduces a comprehensive approach for classifying health service patients based on their satisfaction levels with the aim of enhancing service quality and overall patient experience. The proposed model involved five key steps: questionnaire, data analysis, classification analysis, classification function, action and check. The analytical support for this approach was derived from factor analysis, k-means clustering, and multiple discrimination analysis. In this study, 288 valid responses were collected from medical and dental clinics in Brazil, which comprised a convenience sample. This approach identified four quality factors – interaction, physical environment, service outcome, and waiting time – and two patient groups based on satisfaction levels, highlighting service outcome and waiting time as pivotal factors in patient clustering. This study addressed the challenges of identifying target patient groups and classifying them to enhance satisfaction while maintaining the quality of healthcare services. Future studies could replicate this methodology by incorporating variables that capture client-specific organizational relationships. This will contribute to refining strategies for enhancing service quality and patient satisfaction in diverse healthcare settings.