Interoperable Health Information Exchange
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Aligning with the Standards Development Community: The New Cycle for Standards Version Advancement Process
As part of ONC’s ongoing charge to coordinate across federal and industry stakeholders, we determined it was necessary to adjust our Standards Version Advancement Process (SVAP) timeline. Although it may seem like this process has been around for a while, it’s still brand new and we’ve been looking at ways to optimize how the process aligns with other standards development work in the community. The changes we’ve made will help ensure timely publication of implementation specifications central to our cadence for new versions of USCDI.
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InterSystems Successfully Completes eHealth Exchange Product Testing to Ensure Interoperability
InterSystems...today announced that the InterSystems HealthShare® informatics platform has successfully completed the eHealth Exchange Product Testing Program. As an eHealth Exchange Validated product, HealthShare supports a common set of standards and specifications that enable a secure, trusted, and interoperable connection among all participating eHealth Exchange organizations for the standardized flow of information, benefiting millions of patients. Read More »
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Multiple New Reports on Interoperability Released
Two new reports on interoperability, and a related Call to Action were released in fall 2017 with potential impact on public health. The reports focus on the perceived successes and barriers to health information exchange and interoperability. We draw out the relevance of these reports to public health as well as some of our own observations on these issues from a past working paper. The Call to Action released by the Health Information Management and Systems Society (HIMSS) calls on the Department of Health and Human Services (HHS) to demonstrate leadership and promote progress in a number of key areas.
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The Importance of High Quality Data for Artificial Intelligence Reliability
Artificial Intelligence (AI) is a hot topic right now in medical practice. Though there are many reasons why AI solutions have become so popular, one of the biggest reasons is that AI has the potential to reduce clinical burnout and fatigue by improving Clinical Decision Support in electronic health record (EHR) systems. To understand how this can be achieved, we must first understand what AI is and how it works...For Healthcare, AI and Machine Learning algorithms must rely on copious amounts of granular, high-quality data.
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