Abstract:
In recent times, the increasing healthcare spending due to the rising health awareness signifies the importance of identifying the appropriate factors that influence patient satisfaction, weight assignment to these factors, and measurement of patient satisfaction becomes important. However, devising a robust objective weighting method for weight assignment of the factors and an analytical method for determining patient satisfaction scores has not been paid enough attention. Motivated by these issues, this work focuses on devising a robust objective weighting method for weight assignment of the factors that influence patient satisfaction, an analytical method for determining patient satisfaction, and real-life implementation. We first propose a joint weighting methodology to allocate the weights to the factors by integrating the weights determined by different objective weighting methods, namely, mean weight, SD, entropy, criteria importance through intercriteria correlation, and preference selection index-based approaches. Next, using the weights of these factors, we design a modified weighted aggregated sum product assessment method to determine a single patient satisfaction score by integrating the scores obtained from the weighted sum model and the weighted product model. The proposed methodology is applied to a real-world dataset provided by a large healthcare provider and diagnostic clinic in Kolkata, India, to exhibit the real-life implementation. The theoretical insights obtained through non-parametric tests highlight the significant difference between joint weighting-based and single weighting-based methods. The context-specific insights signify that the patients suffering from arthritis and hyperlipidaemia exhibit lower satisfaction. Also, the patients suffering from dengue express lower satisfaction than the patients suffering from malaria. Additionally, the healthcare provider should focus on improving the service quality of the departments such as ophthalmology, ENT, and dietician.