Model Formulation: HL7 Clinical Document Architecture, Release 2

By R. Dolin, L. Alschuler, S. Boyer, C. Beebe, F. Behlen, P. V. Biron, A. Shabo. J. Am. Medical Informatics Assoc., 2006

796 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Health Information Management, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/a50c868af23cbb2c06330b69933cd621d707c868

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Serguei V. S. Pakhomov
2. Gunther Lenz
3. S. Rosenbloom
4. Olivier Bodenreider
5. Douglas C. Schmidt
6. Jun Xia
7. Guang Yang
8. Peng Zhang

In Health Information Management

1. S. Rosenbloom
2. Olivier Bodenreider
3. Jun Xia
4. Guang Yang
5. Qinghao Ye

In Molecular Biology

1. Olivier Bodenreider
2. Ozlem Uzuner
3. Christopher Kotfila
4. Yuan Luo
5. Byron C. Wallace
6. Atul J. Butte
7. Sanda M. Harabagiu
8. Travis R. Goodwin

Citations in the corpus

• Investigating Longitudinal Tobacco Use Information from Social History and Clinical Notes in the Electronic Health Record (2016, methodology): “We evaluated adequacy of several existing models including HL7 CDA-based models 20 and openEHR 21 archetypes for representing social history information.”
• FHIRChain: Applying Blockchain to Securely and Scalably Share Clinical Data (2018, background): “ur future research in this space. 25 May not be compatible with legacy systems not supporting FHIR. Many legacy systems may use other messaging standards, such as the more prevalent HL7 v2 standards [57], and do not support FHIR protocols. The goal of this paper, however, is to present the underlyin”
• Electronic health records: new opportunities for clinical research (2013, background): “Thirdly, HL7 Reference Information Model (RIM) and HL7 Clinical Document Architecture (HL7 CDA) [26] are designed to communicate a single clinical document as a message and are therefore ideally suited to a messaging environment in which HL7 version 3 is already in use for other purposes, and where…”
• Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond (2021, positive): “However, the creation of interoperable systems that follow the requirement for the representation of clinical knowledge is important for the broad adoption of such technology [106].”
• Biomedical Ontologies in Action: Role in Knowledge Management, Data Integration and Decision Support (2008, background): “The HL7 Clinical Document Architecture, Release 2 (CDA R2) model is "richly expressive, enabling the formal representation of clinical statements", including clinical observations, medication administrations, and adverse events [120].”
• Normalized names for clinical drugs: RxNorm at 6 years (2011, positive): “Recommended by HITSP, RxNorm is the designated vocabulary to represent ‘Medication Brand Name,’ ‘Medication Clinical Drug Name,’ and ‘Allergy/Adverse Event Product’ (if the product causing the adverse event is a medication). RxNorm names and codes are used to represent medication names in the Contin”