The interoperability of medical data is massively important.

Melissa Informatics helps organizations, health care professionals and clinical informaticians interact with FAIR data: Findable, Accessible, Interoperable & Reusable. outlines the needs and requirements for next generation tools with three goals for healthcare data interoperability:

Realize the vision of a learning health system where individuals are at the center of their care and providers have a seamless ability to securely access and use health information from different sources.

To provide access to individuals health information, which is stored in electronic health records (EHRs), but includes information from many different sources and portrays a longitudinal picture of their health.

Helping public health agencies and researchers rapidly learn, develop, and deliver cutting edge treatments.

According to section 4003 of the 21st Century Cures Act, the term 'interoperability,' with respect to health information technology, means such health information technology that— "(A) enables the secure exchange of electronic health information with, and use of electronic health information from, other health information technology without special effort on the part of the user; "(B) allows for complete access, exchange, and use of all electronically accessible health information for authorized use under applicable State or Federal law; and "(C) does not constitute information blocking as defined in section 3022(a)."

Melissa Informatics tools simplify integration processes and greatly enable long term data interoperability and extensibility.

Machine reasoning enabled systems offer enhanced understanding through inferred linkages to reveal new insights not previously identified, satisfying the concept of a ‘learning health system’.

Our improved drag and drop ‘coordination without cooperation’ offers integration for existing data sources that minimizes centralized warehousing requirements and avoids creating expensive new “data tombs”.

By rooting out and finding data wherever it can be found, we preserve the sanctity of personally identifiable information (PII) and conform to HIPPAA regulations.

The ability to apply multiple ontologies and lexicons allows re-centering of focus, connections and terminologies thereby providing insight in multiple contexts from the same data sets.

Our approach allows users to effectively profile and communicate with data as required, be it Discovery-centered, Drug-centered, Patient-centered, or Consumer-centered, while maintaining compliance.

Widely accepted as the most thorough and best way to draw inferences and conclusions from data, visual analytics offers clinicians a single view of as many relevant studies and findings available from different data formats brought into a visual presentation.

The researcher can characterize, evaluate, and refine clinical processes, then develop, implement, and refine clinical decision support systems.

Melissa Informatics leads the procurement of information, customization, development, implementation, management, evaluation, and continuous improvement of clinical information systems.

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