Lean service quality improvement for enhancing medical tourism using a dual-stage approach in healthcare

The study investigates the dimensions that contribute to a remarkable service quality improvement model aimed at explaining and predicting key factors influencing healthcare service quality. It employs a dual approach of Structural Equation Modeling (SEM) and Artificial Neural Networks (ANN) to develop a model that identifies dimensions significantly impacting patient satisfaction and medical tourism in Ethiopia. Additionally, sensitivity analysis is used to rank these dimensions, providing better insights and alternatives. A total of 225 patient data points were collected from respondents through a questionnaire to develop a lean service quality framework using SPSS, AMOS, and ANN. The RMSE value of the ANN model (0.88) indicates good predictive accuracy for the lean service quality improvement model. According to the sensitivity analysis ranking from the ANN, the most significant predictors are service quality and lean service quality. The study integrated lean thinking, service quality, and patient satisfaction to enhance medical tourism using SEM and ANN. It also ranked the importance levels of the lean service quality improvement dimensions through ANN sensitivity analysis.