Telemedicine is a technology that can make it easier for patients to interact with doctors through online media. The influence of the doctor on the patient in real life can occur physiologically at any time. Therefore, patients must choose a suitable doctor to communicate with to get the right and appropriate health services. Many previous studies have focused on patient-physician matching, but such technical implementations have not been carried out in many healthcare, especially the remote healthcare domain. Currently, the selection of doctors for telemedicine depends only on the available doctor information while the number of doctors there is not small, which causes patients difficulties in choosing a doctor. The recommendation system can be helpful in providing doctor recommendations. This study created software that can provide recommendations for matching doctor patients in telemedicine using a hybrid filtering method that combines two methods, namely the collaborative filtering method using rating parameters and the Content-based filtering method using the availability of content contained in the doctor's profile. The study was conducted on the get-well app. From the results of the calculation process that has been carried out, the content-based filtering method can recommend new doctors who have never treated patients and have no previous ratings, while collaborative filtering methods can recommend doctors who have a history and have had a rating from patients. After the implementation, we conducted a test of accuracy. The test was carried out using a confusion matrix with the accuracy results obtained, which was 91 %. In these results, the hybrid filtering method can help choose the right doctor according to the criteria and needs of the patient. For future research, it can use other parameters in providing recommendations, such as comments or likes and dislikes.