Health Data Standards
"Health data standards are key to the U.S. quest to create an aggregated, patient-centric electronic health record; to build regional health information networks; to interchange data among independent sites involved in a person’s care; to create a population database for health surveillance and for bioterrorism defense; and to create a personal health record." [1]
Health data standards and interoperability are essential for the seamless exchange and interpretation of data within and across systems and organizations to address the issue of having "too many ways to say the same thing" (e.g., Health Data sources such as electronic health record [EHR] systems across different hospitals and health systems).
There are different levels of standards and interoperability including "syntactic" (structure or format) and "semantic" (content or meaning). Common data models (CDM) such as the Observational Medical Outcomes Partnership (OMOP) CDM are an example of syntactic standards [2]. Terminologies, vocabularies, or coding systems defined in the United States Core Data for Interoperability (USCDI) are examples of semantic standards [3]. These include:
ICD-10-CM (International Classification of Diseases, Tenth Revision, Clinical Modification) for diagnoses
CPT (Current Procedural Terminology) for procedures
LOINC (Logical Observation Identifiers Names and Codes) for laboratory tests, clinical observations, etc.
RxNorm for medications
SNOMED CT (Systematized Nomenclature of Medicine Clinical Terms) for clinical data in EHR systems
Syntactic and semantic standards are developed and maintained by numerous Standards Development Organizations (SDOs) [1]. Founded in 1987, HL7 International is a major SDO that provides a framework and standards for exchange, integration, sharing, and retrieval of electronic health information (e.g., in EHR systems). HL7 primary standards for integration and interoperability include Version 2.x (or V2), Version 3.x (or V3), CDA (Clinical Document Architecture), and Fast Healthcare Interoperability Resources (FHIR) [4].
See CODIAC for Health chapter on Observational Research with EHR Data for more information.
References
Hammond WE. The making and adoption of health data standards. Health Aff (Millwood). 2005 Sep-Oct;24(5):1205-13. doi: 10.1377/hlthaff.24.5.1205. PMID: 16162564.
Weeks J, Pardee R. Learning to Share Health Care Data: A Brief Timeline of Influential Common Data Models and Distributed Health Data Networks in U.S. Health Care Research. EGEMS (Wash DC). 2019 Mar 25;7(1):4. doi: 10.5334/egems.279. PMID: 30937326; PMCID: PMC6437693.
Bodenreider O, Cornet R, Vreeman DJ. Recent Developments in Clinical Terminologies - SNOMED CT, LOINC, and RxNorm. Yearb Med Inform. 2018 Aug;27(1):129-139. doi: 10.1055/s-0038-1667077. Epub 2018 Aug 29. PMID: 30157516; PMCID: PMC6115234.
Braunstein ML. Healthcare in the Age of Interoperability: The Promise of Fast Healthcare Interoperability Resources. IEEE Pulse. 2018 Nov-Dec;9(6):24-27. doi: 10.1109/MPUL.2018.2869317. PMID: 30452344.
Resources
Books/Chapters
Articles
Bodenreider O. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res. 2004 Jan 1;32(Database issue):D267-70. doi: 10.1093/nar/gkh061. PMID: 14681409; PMCID: PMC308795.
Reich C, Ostropolets A, Ryan P, Rijnbeek P, Schuemie M, Davydov A, Dymshyts D, Hripcsak G. OHDSI Standardized Vocabularies-a large-scale centralized reference ontology for international data harmonization. J Am Med Inform Assoc. 2024 Feb 16;31(3):583-590. doi: 10.1093/jamia/ocad247. PMID: 38175665; PMCID: PMC10873827.
Wei WQ, Bastarache LA, Carroll RJ, Marlo JE, Osterman TJ, Gamazon ER, Cox NJ, Roden DM, Denny JC. Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record. PLoS One. 2017 Jul 7;12(7):e0175508. doi: 10.1371/journal.pone.0175508. PMID: 28686612; PMCID: PMC5501393.
Links
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