Electronic Health Record (EHR) holds immensely sensitive information and consisting of crucial data related to the patients. Storing and organizing such data is highly arduous task. Researches still going on to improve the Quality of Service (QOS) of such data. Existing study focused only on improving the system throughput, privacy and latency issues. But they did not tend to scrutinize the scalability and privacy of such data records. In this paper, we propose a novel deep learning framework to improve the Quality of Service using block chain technology. Initially the data is classified into high priority and low priority based on its nature by using Recurrent Neural Network (RNN). Then, the classified high priority data is further allowed to each block of a block chain and the low priority data is stored and maintained as log file. Finally, the results are compared based on the evaluation metrics which demonstrates our proposed novel deep learning framework achieves better accuracy.