Exploring common data model coverage of nursing flowsheet data: a pilot study using SNOMED CT and LOINC mapping
This mapping study identifies a significant gap in integrating nursing data into a national common data model, highlighting an opportunity to enhance patient care through improved real-time insights and evidence-based nursing practices. Addressing this gap can help shape policies that prioritize the inclusion of nursing data. Additionally, aligning nursing data at scale can advance research, increase efficiency, and optimize nurse-sensitive patient outcomes.
Authors
- Robin Austin (ORCID: https://orcid.org/0000-0003-1993-4623)
- Melissa D. Pinto (ORCID: https://orcid.org/0000-0002-1003-180X)
- Elizabeth E. Umberfield (ORCID: https://orcid.org/0000-0001-5029-1158)
- Matthew Byrne (ORCID: https://orcid.org/0000-0003-2510-1337)
- Kathleen Stewart (ORCID: https://orcid.org/0000-0002-2236-381X)
- Malin Britt Lalich
- Jonna Zarbano
Institutions
- University of Minnesota (US)
- Mayo Clinic (US)
- Mayo Clinic in Arizona (US)
- Mayo Clinic Hospital (US)
- Mayo Clinic in Florida (US)
Publication Details
- Journal
- JAMIA Open
- Published
- 2025-11-03
- DOI
- https://doi.org/10.1093/jamiaopen/ooaf168
- Primary Topic
- Nursing Diagnosis and Documentation
- Type
- article
- Field-Weighted Citation Impact
- 0.00