Read

“This article describes lessons learned from the collaborative creation of logical models and standard Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) profiles for family planning and reproductive health. The National Health Service delivery program will use the FHIR profiles to improve federal reporting, program monitoring, and quality improvement efforts.” Matney, S. A., Heale, B., Hasley, S., Decker, E., Frederiksen, B., Davis, N., Langford, P., Ramey, N., & Huff, S....

“Social determinants of health (SDH) are a valuable source of health information which still are not fully utilized in the clinical space.” Watkins, M., Viernes, B., Nguyen, V., Rojas Mezarina, L., Silva Valencia, J., & Borbolla, D. (2020). Translating Social Determinants of Health into Standardized Clinical Entities. Studies in health technology and informatics, 270, 474–478. https://doi.org/10.3233/SHTI200205 PubMed Source Notes coming soon…

“The Multi-State EHR-Based Network for Disease Surveillance (MENDS) is a population-based chronic disease surveillance distributed data network that uses institution-specific extraction-transformation-load (ETL) routines. MENDS-on-FHIR examined using Health Language Seven’s Fast Healthcare Interoperability Resources (HL7® FHIR®) and US Core Implementation Guide (US Core IG) compliant resources derived from the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) to create a standards-based ETL pipeline.” Essaid, S., Andre, J., Brooks, I. M., Hohman, K....

“The Fast Healthcare Interoperability Resources (FHIR) and Clinical Document Architecture (CDA) are standards for the healthcare industry, designed to improve the exchange of health data by interoperability. Both standards are constrained through what are known as Implementation Guides (IG) for specific use.” Tanjga, N., & Krauss, O. (2024). Dual Implementation Guides in FHIR and CDA. Studies in health technology and informatics, 313, 49–54. https://doi.org/10.3233/SHTI240011 PubMed Source Notes coming soon…

“Some researchers see superhuman qualities in artificial intelligence. All scientists need to be alert to the risks this creates.” Why scientists trust AI too much - and what to do about it. (2024). Nature, 627(8003), 243. https://doi.org/10.1038/d41586-024-00639-y PubMed Source Notes coming soon…