Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Methods of Documentation VII: EMR01:30

Methods of Documentation VII: EMR

830
Electronic Medical Records (EMRs) primarily center around electronically documenting patients' health information within a single healthcare organization or practice. They contain essential clinical data related to a patient's medical history, diagnoses, medications, treatment plans, lab results, and other pertinent information relevant to the specific encounter or episode of care. EMRs are designed to streamline documentation and workflow processes within individual healthcare...
830
Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

824
Health Information Technology (HIT)
Health Information Technology, commonly called HIT, integrates advanced information systems and technology in healthcare settings. Its primary functions include:
824
Data Reporting and Recording01:24

Data Reporting and Recording

4.6K
Reporting and recording are crucial in data documentation. The timely, thorough, and accurate documentation of facts is essential when recording patient data. Failure to record findings during an assessment or interpretation of a problem will result in loss of information and make the patient document unreliable. The reader is left with general impressions if the information is not specific. A recording is documenting data of the individual's health information in a traceable, secure, and...
4.6K
Methods of Documentation V: CBE01:23

Methods of Documentation V: CBE

894
Charting by Exception, or CBE, is a method of documentation used in healthcare, particularly in nursing, that focuses on documenting only significant or abnormal findings rather than recording every detail. This approach aims to streamline the documentation process, improve efficiency, and ensure that healthcare providers can quickly identify deviations from normalcy in patient assessments.
In CBE, healthcare professionals establish predefined standards of practice that define what constitutes...
894
Ethical Standards I01:25

Ethical Standards I

791
The American Nurses Association (ANA) created and implemented the first nationally accepted Code of Ethics for Nurses with Interpretive Statements. The Code of Ethics is a living document regularly updated by the ANA and establishes an ethical standard that is non-negotiable for nurses in all roles and settings.
The Code of Ethics provisions outline the nurse's duty to the patient, the healthcare team, the profession, and society. The Code's fundamental principles include advocacy,...
791
Integrated Healthcare System01:20

Integrated Healthcare System

1.6K
An integrated healthcare system (IHS) is a set of organizations that provides for or arranges to provide coordinated and continuous service to a defined population. The IHS takes responsibility for that particular population's health status and outcome, both clinically and fiscally. An integrated healthcare system is a well-organized, well-coordinated, and collaborative network. The integrated delivery system is a network that connects different healthcare providers to deliver organized,...
1.6K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

AI for Radiology: A Primer Part II. Interacting with AI Results.

Radiology·2026
Same author

John Lorber and spina bifida.

Archives of disease in childhood·2026
Same author

Radiology Reimagined: Interoperability and Lessons Learned from the Imaging AI in Practice Demonstration.

Radiology·2026
Same author

Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline.

Diagnostic and interventional radiology (Ankara, Turkey)·2026
Same author

Guidelines for Reporting Studies on Large Language Models in Radiology: An International Delphi Expert Survey.

Radiology·2026
Same author

Agentic AI in Radiology: Evolution from Large Language Models to Future Clinical Integration.

Radiology. Artificial intelligence·2026

Related Experiment Video

Updated: Jun 23, 2025

Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions
06:18

Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions

Published on: April 5, 2024

1.0K

Standardizing imaging findings representation: harnessing Common Data Elements semantics and Fast Healthcare

Ali S Tejani1, Brian Bialecki2, Kevin O'Donnell3

  • 1Department of Radiology, UT Southwestern Medical Center, Dallas, TX 75390, United States.

Journal of the American Medical Informatics Association : JAMIA
|June 20, 2024
PubMed
Summary

This study introduces a framework using Common Data Elements (CDEs) and Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) to standardize radiology results. This enables seamless integration of human and AI-generated data for improved patient care.

Keywords:
Common Data ElementsHealth Level 7observation resourceradiologystandards

More Related Videos

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.1K
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

15.9K

Related Experiment Videos

Last Updated: Jun 23, 2025

Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions
06:18

Author Spotlight: Segmentation and VR for Advanced Neurovascular Interventions

Published on: April 5, 2024

1.0K
Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
07:13

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

1.1K
A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
07:50

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts

Published on: September 20, 2018

15.9K

Area of Science:

  • Medical Informatics
  • Radiology Data Standards
  • Health Data Interoperability

Background:

  • Radiology results are often unstructured, hindering data integration and downstream system use.
  • Standardizing semantic labels and data structures is crucial for efficient healthcare data exchange.
  • Current systems struggle to integrate radiologist-created reports with AI-generated findings.

Purpose of the Study:

  • To design a framework for representing radiology results in a standards-based data structure.
  • To utilize joint Radiological Society of North America/American College of Radiology Common Data Elements (CDEs) as semantic labels.
  • To enable integration of radiologist and AI-generated data for downstream systems.

Main Methods:

  • Developed a framework modeling radiology findings as HL7 FHIR observations.
  • Employed CDE set/element identifiers as standardized semantic labels for findings and attributes.
  • Integrated CDE identifiers with RadLex, SNOMED CT, and LOINC ontologies within FHIR DiagnosticReport resources.

Main Results:

  • Radiology findings can be labeled as discrete data using CDE definitions for semantics and FHIR observations for structure.
  • CDE-encoded observations provide consistent labels for diagnoses, recommendations, and quantitative data.
  • Demonstrated framework application by encoding pulmonary nodules on chest CT for workflow exchange.

Conclusions:

  • CDE-labeled FHIR observations create a common language for encoding and exchanging radiology data.
  • This facilitates the use of individual radiology findings across healthcare systems.
  • Standardized radiology data enhances value and utility throughout patient care.