The importance of the healthcare industry, benefiting from the synergies between sciences, adds to the necessity of discovering knowledge, which is achievable with big data analytics tools. The purpose of this article is to examine the challenges and provide solutions for using big data in the healthcare industry. The methods of this article are derived from PRISMA guidelines and its models. A variety of databases and search engines including PubMed, Scopus, Elsevier, IEEE, Springer, Web of Science, Proquest, and Google Scholar were searched according to credible keywords. The results of the present study showed that the problems associated with the use of big data in the healthcare industry could be classified in four groups including "data gathering, storage and integration", "data analysis", "knowledge discovery and information interpretation", and "infrastructure". Although the results point to a high frequency of challenges in the "data gathering, storage and integration" group, the greatest weight of problems, due to their importance, appears to be visible in the "infrastructure" group. Considering the numerous benefits of using big data, it is imperative to identify the challenges and resolve them accurately. It is expected that all the barriers can be removed soon. Big data analytics tools will be able to offer the best possible strategies based on human individual and social conditions in the context of artificial intelligence methods.


Big data, Data analysis, Data integration, Internet Of Things (IOT), Medical informatics, Biological informatics