Quality management techniques such as the quality function deployment model can help hospitals assess and improve the quality of their services by integrating the voice of customers. The different quality parameters of this model are usually determined and assessed by experts; nonetheless, obtaining such experts is not always easy or inexpensive. Moreover, in this method, patient opinions are not usually considered directly, although they are the real users of the services and those who can best assess those services. Nevertheless, these opinions are easily accessible today, owing to the development of medical social networks where patients directly convey their opinions about the different services and features of a hospital. Therefore, it is feasible to replace expert knowledge with the information provided by these opinions. Based on this idea, this study proposes a novel fuzzy recommendation model based on the quality function deployment method to rank hospitals depending on patient opinions and preferences regarding hospital services. This model integrates a topic modeling strategy for determining hospital requirements, customer needs, and the relationship between them as well as a sentiment analysis algorithm for assessing customer satisfaction regarding hospital services. To demonstrate the usefulness of the proposed method, several experiments were conducted using patient reviews from real hospitals, and the method was compared against other recommendation models. The results prove that this approach represents a step toward more personalized and effective health care system selection considering patient preferences and opinions.