Transforming Modern Healthcare Through Big Data Analytics: Opportunities, Challenges, and Future Innovations

Swapnil Arun Gaikwad

Abstract: In order to have a better understanding of the issue under discussion, I did some Background: reading of various scientific literature concerning the ways doctors process information. The particular attention was paid to the differences between user-friendly structured electronic charts and rather hard-to-process unstructured information including handwritten records and blurry scans. My findings suggest that by applying modern technological solutions to analyze information more efficiently, we can diagnose the disease at an early stage. Furthermore, it allows avoiding using "one size fits all" approach and creating personalized treatment programs. Moreover, for business reasons, hospitals will be able to predict their peaks and plan the necessary resources properly. However, it is not always smooth sailing. There are major hindrances in the research. Setting up such systems is very costly, and the issue of maintaining the privacy of patient data is of great concern. Moreover, there is a shortage of skilled personnel who have expertise in both healthcare and information technology. Ultimately, what is suggested in this paper is that, even though innovations like artificial intelligence and the "Internet of Things" will definitely contribute significantly to the future development of healthcare, the underlying issues related to privacy and cost will need to be addressed before such transformations can take place. This would enable a shift from a reactive approach to proactive healthcare provision.

Keywords: Big data, big data analytics, healthcare, predictive analytics, electronic health records, patient care, data mining