Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Drug Dissolution: Requirements and Profile Comparison

The acceptance criteria for dissolution profile data are anchored in Q values, representing the percentage of drug dissolved within a specified period. This assessment unfolds in three stages:First Stage: The test passes if all six drug dosage units are equal to or greater than Q plus 5%; otherwise, the sample proceeds to the second stage.Second Stage: The average of twelve units must be equal to or greater than Q, with no unit falling below Q - 15% to pass; if not, it progresses to the final...

Data: Types and Distribution

Data: Types and Distribution

In biostatistics, data are the observations collected for analysis. There are two main types: parametric and non-parametric. Parametric data, which include continuous (e.g., weight) and discrete numerical data (e.g., number of tablets), assume a particular distribution pattern, often the normal distribution. Non-parametric data do not adhere to a specific distribution and typically comprise nominal (e.g., gender) and ordinal categorical data (e.g., pain scale ratings).
Distributions in...

Mass Analyzers: Common Types

Mass Analyzers: Common Types

The quadrupole mass analyzer consists of four cylindrical metal rods arranged in a diamond carrying a DC voltage and a radio-frequency AC voltage. The motion of ions through the quadrupole depends on the field strength, causing only ions of a certain m/z to resonate successfully and strike the detector at a given field strength. Though the transmission rate for these analyzers is high, the exact elemental composition of the sample is not determined because of low resolution; however, they are...

Profile Leveling and Cross Sections

Profile leveling and cross-sections are surveying methods used to determine and document terrain elevations for infrastructure projects such as highways, railroads, canals, and pipelines. These methods provide data for earthwork planning and alignment of proposed routes. Profile leveling involves measuring elevations along a fixed line to create a vertical terrain profile. A surveyor sets up a leveling instrument at the benchmark (BM) and records a backsight (BS) to determine the instrument's...

Mechanical Characteristics of Steel

Mechanical Characteristics of Steel

The mechanical characteristics of steel are assessed through various tests that evaluate its strength, toughness, and flexibility. These tests include tension, torsion, impact, bending, and hardness assessments, each providing crucial information about steel's suitability for specific applications.
The tension test is fundamental for determining tensile strength. In this test, a steel specimen is stretched using a gripping device until it breaks. The data collected during this test are used to...

How Data are Classified: Numerical Data

How Data are Classified: Numerical Data

Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...

You might also read

Related Articles

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

Sort by

Same author

Beyond the algorithm: health technology assessment frameworks for AI in cardiology under the European Union Health Technology Assessment Regulation: a systematic review.

Annals of translational medicine·2026

Same author

Health Data Quality Skill Gaps and Training Needs Among European Health Data Stakeholders: Cross-Sectional Survey.

Journal of medical Internet research·2026

Same author

Addressing Data Quality Challenges in Lung Cancer Data Within the Observational Medical Outcomes Partnership Common Data Model: Observational Study.

Journal of medical Internet research·2026

Same author

Assessment of the ADLIFE intervention as a digital solution for patients with advanced chronic diseases: a quasi-experimental trial.

NPJ digital medicine·2026

Same author

Rethinking Trust in Synthetic Health Data: Lessons From 7 European Research Initiatives.

Journal of medical Internet research·2026

Same author

Regulations for international non-proprietary name prescribing and substitution, relevant for cross-border ePrescribing and eDispensation services in the European Union.

European journal of public health·2025

Search research articles

Related Experiment Video

Updated: May 24, 2026

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

A data types profile suitable for use with ISO EN 13606.

Shanghua Sun¹, Tony Austin, Dipak Kalra

¹University of London, Cranmer Terrace, London SW17 0RE, UK. ssun@sgul.ac.uk

Journal of Medical Systems

|March 9, 2012

Summary

This paper details creating a tailored data type profile for Electronic Healthcare Record (EHR) interoperability. It streamlines ISO 21090 standards for better EHR system communication.

Area of Science:

Health Informatics
Healthcare Information Standards

Background:

ISO EN 13606 specifies Electronic Healthcare Record (EHR) communication standards.
ISO 21090:2010 provides a broad set of data type models for health IT.
Existing standards present overlapping functionalities for EHR data representation.

Purpose of the Study:

To develop a specialized data type profile for EHR interoperability.
To streamline the implementation of ISO 21090 for EHR vendors.
To reduce ambiguity in representing EHR information properties.

Main Methods:

Analysis of ISO EN 13606 and ISO 21090 standards.
Identification of overlapping and redundant data type models.
Development of a curated subset of ISO 21090.

More Related Videos

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data

Published on: May 15, 2019

Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management

Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management

Published on: November 30, 2022

Related Experiment Videos

Last Updated: May 24, 2026

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Executing Complexity-Increasing Queries in Relational (MySQL) and NoSQL (MongoDB and EXist) Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data

Using the Open-Source MALDI TOF-MS IDBac Pipeline for Analysis of Microbial Protein and Specialized Metabolite Data

Published on: May 15, 2019

Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management

Biobank for Translational Medicine: Standard Operating Procedures for Optimal Sample Management

Published on: November 30, 2022

Main Results:

A defined data type profile tailored for EHR interoperability.
Reduced complexity for EHR system vendors.
Enhanced consistency in EHR information representation.

Conclusions:

A targeted profile of ISO 21090 is essential for effective EHR interoperability.
Streamlining data type models improves EHR system integration.
This approach facilitates clearer and more consistent EHR data exchange.