Providing a model based on Recommender systems for hospital services (Case: Shariati Hospital of Tehran)

In the increasingly competitive market of the healthcare industry, the organizations providing health care services are highly in need of systems that will enable them to meet their clients' needs in order to achieve a high degree of patient satisfaction. To this end, health managers need to identify the factors affecting patient satisfaction focus. The purpose of this study is to provide a model based on recommender systems in order to increase patient satisfaction with the quality of hospital services, in which patients were clustered based on personal information and then dimensions of services were weighted to determine the most important dimensions.
Information technology can provide the possibility of moving towards better services by analyzing customer preferences and tailoring the content and process of service provision according to customer needs. On the other hand, the personalization of products and services is one of the most important factors affecting customer satisfaction.
In order to conduct the model, the data related to satisfaction forms of 556 discharged patients from Shariati Hospital in Tehran was used. By estimating the accuracy of the predictions of the model based on the mean absolute error criterion and the mean squared error, the values were respectively obtained as 40% and 49%.
In this study, through weighting the characteristic for different groups of patients, the more important services were identified where considering the number of 148 test data, it was determined that the model of the most important dimensions of the service for each cluster are correctly determined. Therefore, the hospital can decrease dissatisfaction of the new patients in each group through reinforcing the important services in each group, after discharge.