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

Concepts of Health and Illness01:29

Concepts of Health and Illness

Health is a condition of the body, mind, and spirit where an individual remains free from illness. Similarly, wellness is an active state, including living a lifestyle that promotes physical, mental, and emotional health. Physical health is critical for the overall well-being and can be affected by lifestyle, activity level, diet, and behavior. The highest attainable standard of health is a fundamental and universal human right. Consider Lisa, a fifteen-year-old born with congenital...
Health Literacy01:21

Health Literacy

Health literacy is an individual's or a community's capacity to comprehend, receive, read, and use relevant healthcare information and services. The World Health Organization (WHO, 2018) defines health literacy as the cognitive and social skills that determine the ability of individuals to gain access to, understand, and use information in ways that promote and maintain good health. As a result, the WHO helps individuals manage long-term health concerns, participate in preventative programs,...
Models of Health Promotion and Illness Prevention II01:18

Models of Health Promotion and Illness Prevention II

The person's health status fluctuates continually, varying from being in good health to becoming ill and returning to being healthy. To understand the concept of illness prevention, there are two models. First, the health-illness continuum model is a graphic representation of an individual's wellness. It states that a person is considered healthy in the absence of physical disease and the presence of good emotional health.
The agent-host-environment model states that disease results from...
Dimensions of Health and Illness01:21

Dimensions of Health and Illness

The factors influencing the health-illness continuum can be internal or external and may or may not be under conscious control. They are related to the following eight human dimensions, and each dimension is interrelated to one other.
Models of Health Promotion and Illness Prevention I01:25

Models of Health Promotion and Illness Prevention I

A model is a theoretical way to understand a concept or an idea. Models can overcome barriers to health regardless of diverse economic and cultural backgrounds. In addition, models make the task easier by providing different ways to approach complex issues. There are two major health promotion models: the health belief model and the health promotion model.
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...
Documentation in Long-Term and Home Healthcare Setting01:29

Documentation in Long-Term and Home Healthcare Setting

Documentation in long-term care facilities and home healthcare settings is crucial for ensuring continuous, coordinated, and comprehensive care for patients. Each setting has its specific documentation processes and tools:
Long-Term Care Facilities

You might also read

Related Articles

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

Sort by
Same author

An EHR-based framework for modeling growth curves and constructing growth centile charts for genetic disorders.

NPJ genomic medicine·2026
Same author

A New Cancer Diagnosis is Never Good-Patient Choice, Busy Health Systems, and Health Information Access.

JAMA network open·2026
Same author

Machine Learning Estimation of Gestational Age at Delivery Using Linked Mother-Infant Electronic Health Records Across Two Health Systems.

medRxiv : the preprint server for health sciences·2026
Same author

Developing an expanded version of My Diabetes Care in English and Spanish: A design and formative usability study.

Digital health·2026
Same author

Automatic Placement Within a Hierarchical Clinical Decision Support Terminology.

Studies in health technology and informatics·2026
Same author

DeepSeek R1 Distilled Fails to Perform Well Against the USMLE and Other LLMs with and Without Semantics.

Studies in health technology and informatics·2026
Same journal

Machine learning-based prediction of non-ionic iodinated contrast media-induced acute adverse reactions following contrast-enhanced CT.

International journal of medical informatics·2026
Same journal

Integrating diversity, equity, and inclusion in generative AI applications for healthcare education: a scoping review.

International journal of medical informatics·2026
Same journal

Medical students' use of large language models: a national survey.

International journal of medical informatics·2026
Same journal

BlockFedMed: A blockchain-federated learning framework for privacy-preserving mortality prediction across heterogeneous intensive care units.

International journal of medical informatics·2026
Same journal

Integrating clinical decision support systems in pediatric oncology: A scoping review of applications, implementation gaps, and management Implications.

International journal of medical informatics·2026
Same journal

Understanding digital health capability of allied health professionals - a mixed-methods study with content validity analysis.

International journal of medical informatics·2026
See all related articles

Related Experiment Video

Updated: Jun 28, 2026

An Application for Pairing with Wearable Devices to Monitor Personal Health Status
06:58

An Application for Pairing with Wearable Devices to Monitor Personal Health Status

Published on: February 3, 2022

The Health Archetype Language (HAL-42): interface considerations.

Peter L Elkin1, David Froehling, Dietlind Wahner-Roedler

  • 1Mayo Clinic, 200 1st Street SW, Rochester, MN 55905, USA. elkin.peter@mayo.edu

International Journal of Medical Informatics
|October 17, 2008
PubMed
Summary
This summary is machine-generated.

Clinical researchers using the Health Archetype Language (HAL-42) achieved 74.8% agreement in creating epidemiological rules. While HAL-42 is usable, training is needed for high reliability in ad hoc clinical data queries.

More Related Videos

Multicellular Human Alveolar Model Composed of Epithelial Cells and Primary Immune Cells for Hazard Assessment
09:27

Multicellular Human Alveolar Model Composed of Epithelial Cells and Primary Immune Cells for Hazard Assessment

Published on: May 6, 2020

Related Experiment Videos

Last Updated: Jun 28, 2026

An Application for Pairing with Wearable Devices to Monitor Personal Health Status
06:58

An Application for Pairing with Wearable Devices to Monitor Personal Health Status

Published on: February 3, 2022

Multicellular Human Alveolar Model Composed of Epithelial Cells and Primary Immune Cells for Hazard Assessment
09:27

Multicellular Human Alveolar Model Composed of Epithelial Cells and Primary Immune Cells for Hazard Assessment

Published on: May 6, 2020

Area of Science:

  • Health Informatics
  • Clinical Research
  • Medical Ontology

Background:

  • Clinical research rule creation can be complex and subjective.
  • Standardized languages and ontologies are crucial for reliable data analysis.
  • The Health Archetype Language (HAL-42) facilitates real-time epidemiological inquiry using health ontologies.

Purpose of the Study:

  • To evaluate the inter-rater reliability of clinical research rule creation using HAL-42.
  • To assess the usability of HAL-42 for encoding and running epidemiological inquiries.
  • To determine if rule complexity impacts agreement among subject matter experts (SMEs).

Main Methods:

  • Four SMEs independently created and executed 10 rules using HAL-42.
  • SNOMED CT was used as the underlying health ontology.
  • The study involved a population of 17,731 patients with 50,000 fully encoded clinical records.

Main Results:

  • Inter-rater agreement was 74.8% with a Kappa statistic of 0.49217.
  • No significant difference in agreement was found between easy and complex rules.
  • SMEs demonstrated comparable competence in executing both simple and complex queries.

Conclusions:

  • HAL-42 is sufficiently usable for achieving reasonable inter-rater reliability in clinical research rule creation.
  • Training is recommended to enhance reliability for ad hoc queries.
  • SMEs are equally adept at handling both simple and complex queries on ontologically indexed clinical data.