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MS DataConnect

MS DataConnect

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Our mission

The mission of MS DATACONNECT is for data to achieve maximal impact. We aim to transform the (mostly population based) management of today’s healthcare into an individualized, personalized and precision level management. We believe the key to achieve this next generation management is FAIR data. FAIR stands for Findable, Accessible, Interoperable and Re-usable.

Our vision

Four work packages are defined: we aim to develop  1° data collection procedures and tools to create data that is FAIR (=findable, accessible, interoperable and re-usable), 2° IT solutions to allow (temporarily) pooling and linking of FAIR dataset, 3° statistical methods to define minimal requirements for datasets and 4° new analytical methods for optimal mining of connected and pooled FAIR datasets. These work packages are implemented on 3 different levels: 1° A local level: a proof-of-concept study in which retrospective data from 6 partners involved in care, rehabilitation and research are connected into a multidisciplinary data infrastructure; 2° A national level: in collaboration with the healthdata.be platform and all relevant stakeholders (e.g. National MS society and the Belgian MS Study Group), we aim to develop a Belgian national multidisciplinary MS repository using FAIR data collection procedures and IT solutions. We strive towards an “only-once principle” referring to data capture from primary (and operational sources) of health care actors and re-use of previously collected data; 3° An international level: we are the project coordinators of the MS Data Alliance, a project on better exploitation of real world evidence data driven.

Our values


Improve healthcare!

We aim towards personalized and precision healthcare management

We value patient autonomy and believe in patient-relevant healthcare

We strive towards continuity of care

Enable & encourage collaborations!

We facilitate collaborative multidisciplinary research

We explore opportunities to collaborate with the broader scientific community

We wish to support decisions by regulators, health technology assessment bodies and payers with our data

Secure safety!

We prioritize safe storage and sharing of data

We respect ethical and legal restrictions of data sharing

Guarantee quality!

We prioritize cutting edge- and high-quality research

We continuously explore opportunities to enhance data quality

We strive towards improving the quality of our data collection tools

We follow the “only-once principle” (no need to enter data more than one time) We focus on tools with minimal data collection effort without compromising quality

Be transparent!

We consult our partners for all major decisions

We are transparent in our research and activities

We provide regular feedback to all stakeholders involved

We implement open source IT codes as much as possible

We encourage publication of scientific results in open access journals