Harmonisation strategies for real-world multiple sclerosis data sources

Harmonisation strategies for real-world multiple sclerosis data sources

(Tina Parciak - ongoing since January 2020)

RWD real-world data (RWD) in multiple sclerosis is a valuable source of information for insights into the disease and the potential in scaling up MS RWD is high. Due to the distributed and often lower numbers of patients within those RWD sources, a joint approach in generating real-world evidence (RWE) is beneficial.

When wanting to use RWD in MS in order to generate valuable RWE, we face several challenges. One main challenge will be the driver for the objectives of this PhD: There is no uniform „language“ between registries and cohorts in MS with regards to content (variables) or structure (representation). This heterogeneity results in most registries and cohorts not being ready for (instant) collaboration or large-scaling their data for joint, global analyses.

The chosen manner of the PhD to progress in solving the challenge of heterogeneity is the introduction of dedicated harmonisation strategies:

1. Enabling and supporting (large-scale) collaboration within the MS community through 

• the promotion of harmonisation and use of minimal and core datasets in MS and
• the establishment of a dedicated general MS core dataset.

2. Enabling and supporting (large-scale) collaboration within and beyond the MS community through

• the promotion of the transformation of MS RWD to the OMOP common data model and
• the establishment of an automated OMOP common data model representation of the general MS core dataset.

These harmonisation strategies are simultaneously the leading objectives of the PhD.

In short, Tina would like to improve the process of data harmonisation, i.e. the standardisation of representation and structure of RWD in MS (coming e.g. from registries and cohorts). For both data custodians and scientists, it should become easier and more transparent to harmonise and understand MS RWD. In addition, the added value of harmonisation should be made clear for all stakeholders involved: collaborative analyses to gain RWE from RWD to improve the care and treatment of people with MS.

Tina is involved in following subprojects:

POC1 of the Flanders AI Research Project (2019-2023)

• Federated infrastructure used in the COVID-19 in MS Global Data Sharing Initiative (GDSI) (= MSDA project)

MS Data Alliance:

• COVID-19 & MS Global Data Sharing Initiative (GDSI)
• Mapping exercise regarding COVID-19 vaccination studies
• MSDA Catalogue
• MSDA Core Dataset
• Switchbox
• Educational program

EHDEN - transforming the MS DataConnect dataset to OMOP-CDM