BELTRIMS: Belgian national data infrastructure for multiple sclerose

Description

Multiple sclerosis (MS) is an inflammatory and degenerative disorder of the central nervous system (CNS), that consists of the brain, spinal cord and optic nerve. The body's own immune system incorrectly attacks the central nervous system (CNS), leading to lesions and scarring and thereby causing variable and unpredictable symptoms. Some examples of clinical symptoms include slurred speech, blurred vision, loss of balance, poor coordination, tremor, numbness, extreme fatigue, problems with memory and concentration, paralysis, and blindness. These symptoms can come and go (so-called relapse) or can progress over time. MS affects more than 700,000 people living in Europe, two to three times as many women as men and is most often diagnosed in people aged 20-40 years. MS varies in severity, from mild symptoms to a disabling condition. Overall cost of MS in Europe to health and social care is estimated to be 15 billion euros per year. The Belgian MS Infrastructure (BELTRIMS) is designed to contribute to optimal healthcare for people with MS in Belgium and beyond. We envision a world where decisions concerning MS treatment (made by clinicians, researchers, regulators and patients) are supported by state-of-art analysis of consistent, long-term and quality real-world data (RWD) collection from and by people with MS. RWD is defined as data derived from a number of sources that are associated with outcomes in a heterogeneous patient population representing the real-world settings (e.g., data collected by physicians and multidisciplinary teams in standard clinical care and longitudinal follow-up). Analysis of this data generates real-world evidence that, in turn, can generate meaningful insights into unmet needs, interventional pathways and the clinical and economic impact on patients and healthcare systems. Despite the increasing reliance on RWD, challenges and limitations exist that complicate the generation, collection and use of this data. Because of the multi-stakeholder interest in the collection of RWD in Belgium in combination with the complexity and time-consuming nature of the collection and analysis of RWD, different Belgian stakeholders are willing to join forces to move towards a sustainable and fit-for-purpose data infrastructure for MS in Belgium.

Resources

Name Format Description Link
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
8 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa
23 https://fair.healthdata.be/dataset/f67f9d44-a778-45b0-9edc-0180570922fa

Tags

  • mesh-d009103
  • communauté-française-(community)
  • deutschsprachige-gemeinschaft-(community)
  • national-institute-for-health-and-disability-insurance-(nihdi)
  • codage,-anonymisation-et-ttp-(ehealth)
  • vlaanderen-(region)
  • rijksregisternummer-(rrn)
  • région-wallonne-(region)
  • franse-gemeenschap-(community)
  • yyyy-2015
  • west-vlaanderen-(province)
  • liège-(province)
  • limbourg-(province)
  • numéro-d'identification-de-la-sécurité-sociale-(niss)
  • belgian-study-group-for-multiple-sclerosis-(bsgms)
  • flemish-brabant-(province)
  • sexe
  • multiple-sclerose
  • icd10-g00–g99
  • communauté-flamande-(community)
  • vlaamse-gemeenschap-(community)
  • brabant-flamand-(province)
  • snomed-ct-24700007
  • belgië-(country)
  • project-in-preparation
  • wallonië-(region)
  • sex
  • codering,-anonimisering-en-ttp-(ehealth)
  • antwerp-(province)
  • communauté-germanophone-(community)
  • waals-gewest-(region)
  • hainaut-(province)
  • luik-(province)
  • région-flamande-(region)
  • yyyy-2019
  • identificatienummer-van-de-sociale-zekerheid-(insz)
  • source-data-at-healthdata.be-(sciensano)
  • landesinstitut-für-kranken-und-invalidenversicherung-(likiv)
  • brabant-wallon-(province)
  • région-de-bruxelles-capitale-(region)
  • numéro-inami
  • belgique-(country)
  • antwerpen-(provincie)
  • riziv-nummer
  • vlaams-gewest-(region)
  • waals-brabant-(province)
  • nidhi-number
  • beveiligde-elektronische-brievenbus-(ehealthbox)
  • walloon-region-(region)
  • duitstalige-gemeenschap-(community)
  • multipele-sclerose
  • yyyy-2020
  • wallonia-(region)
  • healthdata.be-(sciensano)
  • yyyy-2016
  • east-flanders-(province)
  • beneluxa-initiative
  • vlaams-brabant-(province)
  • namen-(province)
  • brussels-capital-region-(region)
  • brussels-hoofdstedelijk-gewest-(region)
  • flandre-occidentale-(province)
  • flandre-orientale-(province)
  • belgium-(country)
  • numéro-de-registre-national-(nrn)
  • yyyy-2018
  • henegouwen-(province)
  • age
  • âge
  • flämische-gemeinschaft-(community)
  • rijksinstituut-voor-ziekte-en-invaliditeitsverzekering-(riziv)
  • sclérose-en-plaques
  • multiple-sclerosis
  • disseminated-sclerosis
  • hospital
  • luxemburg-(province)
  • anvers-(province)
  • leeftijd
  • webservices-consultrr-(ehealth)
  • gender
  • luxembourg-(province)
  • cobrha-common-base-registry-for-healthcare-actor-(ehealth)
  • yyyy-2021
  • institut-national-d'assurance-maladie-invalidité-(inami)
  • flanders-(region)
  • geslacht
  • boîte-aux-lettres-électronique-sécurisée-(ehealthbox)
  • oost-vlaanderen-(province)
  • ziekenhuis
  • walloon-brabant-(province)
  • yyyy-2017
  • namur-(province)
  • limburg-(province)
  • hdbp0070
  • west-flanders-(province)
  • flemish-region-(region)
  • hôpital
  • yyyy-2014
  • französische-gemeinschaft-(community)

Topics

  • HEAL

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