medical centers to speed up the patient's treatment process, buying medicine, availability of medicine in the pharmacy, preventing counterfeit drugs from entering the drug supply chain, and preventing drug hoarding. For this purpose, in this research, using Rapidminer software and K-Means, X-Means, K-Means-H2O, and K-Means-Fast algorithms, medical centers were clustered according to distance and proximity to the hypothetical patient so that the patient could access the nearest treatment center very easily. Among these algorithms, the K-Means-H2O algorithm with a silhouette index of 0.67 was chosen as the best algorithm for clustering these data. Then, when the patient went to the desired treatment center, the corresponding electronic prescription code was issued, based on which the patient could receive the desired medicine by visiting the pharmacy. In addition, to ensure the health of the pharmaceutical supply chain, a radio tag was used to identify the supplied drugs to prevent counterfeit drugs from entering the pharmaceutical supply chain while tracking the drug. Finally, by using Visual Basic software and the design of drug and pharmacy fields, the sale of drugs is monitored to prevent drug hoarding, remove expired drugs from the sales cycle, and also support high-selling drugs and pharmacies through a timely supply of drugs provided by the supervisory body. In addition, a field was created where patients can get all or part of their medicines from the nearest pharmacy.