ONC’s Health Information Technology Advisory Committee: 2022 Recap and a Look Ahead to 2023
Mike Berry | January 19, 2023
The Health Information Technology Advisory Committee (HITAC) plays an important role in ONC activities and objectives. Required by the 21st Century Cures Act, the HITAC has been operational since 2018 and represents a wide range of experts in health IT who inform ONC’s policies and programs.
Read Full Post.2023 ISA Reference Edition Is Here
Andrew Hayden | January 10, 2023
We are excited to continue a New Year’s tradition at ONC with the release of the annual Interoperability Standards Advisory (ISA) Reference Edition! The 2023 ISA Reference Edition, the ninth annual publication, reflects more than 150 comments received by ONC during a 60-day public comment period that closed September 30, 2022.
Read Full Post.ONC Supports Adoption and Implementation of Bulk Data APIs
Alex Kontur | January 4, 2023
In 2017 the Health Level Seven® (HL7) standards development community began exploring the feasibility of standardizing a Fast Healthcare Interoperability Resources® (FHIR) bulk data access application programming interface (API) to facilitate large-scale data transfer between systems.
Read Full Post.Not-So-Hidden Gems in the 21st Century Cures Act Final Rule: Get to Know the Conditions of Certification
Steven Posnack | December 15, 2022
Don’t get me wrong, the information blocking regulations are important, but let’s not forget that the 21st Century Cures Act (Cures Act) and our implementing regulations (Cures Act Final Rule) had a few other impactful provisions. In particular, certain changes to the ONC Health IT Certification Program may seem like “more of the same” for health IT developers, but in reality they are really important and beneficial to clinicians, researchers, and the public alike.
Read Full Post.Back to the Future: What Predictive Decision Support Can Learn from DeLoreans and The Big Short
Kathryn Marchesini | December 13, 2022
In the third blog in our series on artificial intelligence (AI) and machine learning (ML)-driven predictive models (data analytics tool or software) in health care, we discussed some potential risks (sometimes referred to as model harms) related to these emerging technologies and how these risks could lead to adverse impacts or negative outcomes. Given these potential risks, some have questioned whether they can trust the use of these technologies in health care.
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