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Electronic Health Records(EHR) are electronically maintained, linked, collections of allied, patient-related
healthcare information collected during past encounters. They incorporate patient demographic information,
encounter details, laboratory reports, prescription notes, past medical records, and other medical data. EHR creation
is designed to support the future diagnosis, treatment, and decision making in patient care. However, since EHR
technology is a burgeoning science, many facets lie under-used or under-utilized. Current implementations are
confined to national boundaries managed by individual National Health Systems (NHS). Consolidated, universally
interoperable EHR schemes are still a thing for the future; a migratory patient may not have his national EHR
available in distant territories. Further, the examination of operational factors unearthed more inadequacies.
Interoperability-related issues include the limiting network bandwidth causing inordinate delays, diverse local
storage schemes at the various NHS clusters, the related requirement for synchronous vocabulary-related translation
mechanisms at the various NHS-controlled boundaries causing inordinate delays, and the related security and access
issues. These issues arise from the requirement for synchronous, query-messaging nature of information access and
exchange. This paper articulates a novel, sound, and secure methodology for achieving true International
Interoperability and uniform efficiency in ubiquitous Electronic Health Record systems. Utilizing intelligent
machine learning processes, required query-messaging information is meaningfully aggregated enhancing the
relevancy, access speed, and value-derivation from the given data. Asynchronous learning excludes the need for
high available network bandwidth, upload and download delays associated with current synchronous database/cloud
systems. Indeed, this overarching solution ensures seamless synchronous operation and high-end international
interoperability, and would work in any ubiquitous EHR environment
