Without semantic interoperability among disparate healthcare IT systems, sharing remote monitoring data in a useful way is extremely challenging.
IHMI’s mission is to make the world’s growing health data useful and actionable by enabling, creating, and applying common standards to it.
While some connected health projects have achieved a limited version of semantically interoperable remote monitoring data, there is still a long way to go before this data can be considered truly semantically interoperable across healthcare systems. The dream of the average consumer being able to purchase a remote monitoring device, such as a wireles blood pressure cuff, and share that data with multiple health care professionals is, for the most part, not possible.
We discuss the current challenges and opportunities facing organizations and healthcare stakeholders who share the aim of unlocking the potential of remote monitoring data.
I would start looking at a couple of open-source architectures:
Edge X Foundry:
Entity Resolution has been discussed for more than a decade -- this is a "must-have" if explainable and Interpretable AI (especially one derived from stream data) is to become reality. Entity resolution is a fancy term for annotation and building ontologies on the fly.