Sentiment Analysis is a well-known task of Natural Language Processing that has been studied in different domains such as movies, phones or hotels. However, other areas like medical domain remain yet unexplored. In this paper we study different polarity classification techniques applied on health domain. We present a corpus of patient reviews composed by a Dutch part (COPOD: Corpus of Patient Opinions in Dutch) and a Spanish part (COPOS: Corpus of Patient Opinions in Spanish). Experiments have been carried out using a supervised method (SVM), a cross-domain method (OpeNER) and a dictionary lookup method for both languages. Obtained results overcome the baseline in almost all the cases and are higher than other polarity classifiers in patient domain. Regarding the bilingualism, the developed systems for Dutch and Spanish have a similar performance for F1-measure and Accuracy.