Abstract
There is a dearth of interoperability between apps, data streams, and predictability in the healthcare industry for a significant amount of the data generated by multiple digital ecosystems. Real-time data streams can be derived as meaningful and scalable enough to enable real-time healthcare predictive analytics thanks to the new technology approach in distributed messaging and Blockchain, which has become a fundamental component of many healthcare technology stacks. Additionally, absorbing data streams from multiple sources from patterns of data can enhance models that are hampered by complex and lengthy analyses by raising the level of prediction and accuracy. Improved responses, lowered availability requirements, and unified predictive modeling will speed up healthcare interoperability and, in turn, improve diagnosis accuracy, move evidence-based medicine (EBM) in the right direction, and produce other positive effects on healthcare that improve best results and quality.
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