Regulations and Funding to Create Enterprise Architecture for a Nationwide Health Data Ecosystem
The COVID-19 pandemic highlighted the United States' lack of a nationwide infrastructure for collecting, sharing, and using health data, especially for secondary uses (e.g., population health management and public health). The federal government is taking several important steps to upgrade the nation's health data ecosystem-notably, the Centers for Disease Control and Prevention's Data Modernization Initiative and the Office of the National Coordinator for Health Information Technology's Trusted Exchange Framework and Common Agreement. However, substantial barriers remain. Inconsistent regulations, infrastructure, and governance across federal and state levels and between states significantly impede the exchange and analysis of health data. Siloed systems and insufficient funding block effective integration of clinical, public health, and social determinants data within and between states. In this analytic essay, we propose strategies to develop a nationwide health data ecosystem. We focus on providing federal guidance and incentives to develop state-designated entities responsible for the collection, integration, and analysis of clinical, public health, social determinants of health, claims, administrative, and other relevant data. These recommendations include a regulatory clearinghouse, federal guidance, model legislation and templated regulation, funding to incentive enterprise architecture, regulatory sandboxes, and a 3-pronged research agenda. (Am J Public Health. 2024;114(2):209-217. https://doi.org/10.2105/AJPH.2023.307477).
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2024 |
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Erschienen: |
2024 |
Enthalten in: |
Zur Gesamtaufnahme - volume:114 |
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Enthalten in: |
American journal of public health - 114(2024), 2 vom: 11. Feb., Seite 209-217 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Seidman, Gabriel [VerfasserIn] |
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Date Completed 14.02.2024 Date Revised 15.02.2024 published: Print-Electronic Citation Status MEDLINE |
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doi: |
10.2105/AJPH.2023.307477 |
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funding: |
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PPN (Katalog-ID): |
NLM366978330 |
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