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

Principles of Disease Surveillance01:26

Principles of Disease Surveillance

Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
Rapid Identification of Pathogens01:25

Rapid Identification of Pathogens

MALDI-TOF MS has transformed clinical microbiology by offering a rapid and reliable method for pathogen identification. The traditional approach to microbial identification typically involves time-consuming culture techniques and biochemical tests, which can delay the initiation of appropriate antimicrobial therapy. MALDI-TOF MS avoids these delays by using characteristic ribosomal protein mass patterns of microbial cells, enabling accurate species-level identification within minutes.Principle...
Nursing Clinical Information System01:27

Nursing Clinical Information System

Nursing Clinical Information System (NCIS)
A Nursing Clinical Information System (NCIS) is a specialized type of healthcare information system tailored to meet the unique needs of nursing practice. It incorporates the principles of nursing informatics to streamline information management and improve the quality of care delivery.
Critical attributes of NCIS include:
Health Information Technology and Healthcare Information System01:30

Health Information Technology and Healthcare Information System

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

You might also read

Related Articles

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

Sort by
Same author

The Orphanet Nomenclature and Classification of Rare Diseases for Improved Patient Recognition and Data Interoperability: Qualitative and Quantitative Analysis.

JMIR medical informatics·2026
Same author

European Reference Networks as core health structures where referring genetic newborn screening positive infants: an innovative operational research framework.

Frontiers in public health·2026
Same author

Biallelic inactivating variants in the chromatin remodeler DMAP1 cause a syndromic neurodevelopmental disorder.

The Journal of clinical investigation·2026
Same author

Rare disease nomenclature and coding: challenges, systems, and policies in the global context.

Archives of medical research·2026
Same author

European Reference Networks - a flagship activity of the EU in the field of rare and complex diseases: from 2017 to 2025.

Orphanet journal of rare diseases·2026
Same author

Coding systems and monitoring practices across the ERN ReCONNET: insights from a comprehensive survey and unmet needs.

Orphanet journal of rare diseases·2026

Related Experiment Video

Updated: Jun 8, 2026

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells
10:37

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

Published on: August 22, 2025

CEMARA an information system for rare diseases.

Paul Landais1, Claude Messiaen, Ana Rath

  • 1Paris Descartes University, Faculty of Medicine, AP-HP, EA 4067, Department of biostatistics and computer sciences, and Department of genetics, Dermatology unit Necker-Enfants Malades Hospital, Paris, France.

Studies in Health Technology and Informatics
|September 16, 2010
PubMed
Summary

CEMARA, a rare disease information system, collects patient data to analyze epidemiological patterns and improve care. It successfully created a shared platform and ontology, enhancing patient care and research for rare diseases.

More Related Videos

A Murine Orthotopic Bladder Tumor Model and Tumor Detection System
06:23

A Murine Orthotopic Bladder Tumor Model and Tumor Detection System

Published on: January 12, 2017

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Related Experiment Videos

Last Updated: Jun 8, 2026

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells
10:37

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

Published on: August 22, 2025

A Murine Orthotopic Bladder Tumor Model and Tumor Detection System
06:23

A Murine Orthotopic Bladder Tumor Model and Tumor Detection System

Published on: January 12, 2017

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
07:15

Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model

Published on: August 16, 2020

Area of Science:

  • Epidemiology
  • Public Health
  • Medical Informatics

Background:

  • Rare diseases affect fewer than 1 in 2,000 people, with many lacking curative treatments.
  • Over 5,000 to 7,000 rare diseases are identified in Europe, posing a significant public health challenge.
  • Effective management requires robust data collection and analysis systems.

Purpose of the Study:

  • To establish and analyze epidemiological patterns of rare diseases using a web-based information system.
  • To improve the match between national demand for and offer of care for rare diseases.
  • To foster collaboration and data sharing among healthcare professionals and institutions.

Main Methods:

  • Implementation of a n-tier architecture for the CEMARA (Centre d'Évaluation des Maladies Rares) information system.
  • Continuous collection and follow-up of patient records from multiple clinical sites and healthcare professionals.
  • Analysis of epidemiological data and exploration of care demand versus supply.

Main Results:

  • CEMARA registered 56,593 cases from 171 clinical sites involving over 850 healthcare professionals.
  • The system facilitated the sharing of a common platform and ontology with Orphanet.
  • Initiation of new rare disease cohorts for enhanced patient care and research was stimulated.

Conclusions:

  • CEMARA provides a valuable platform for collecting and analyzing rare disease data.
  • The system has successfully promoted collaboration and data standardization.
  • CEMARA contributes to improving patient care and advancing research in the field of rare diseases.