The IBD project

Chronic conditions such as the chronic inflammatory bowel disease, Crohn's disease, diabetes, and COPD are often diagnosed. The diagnosis is usually made at a young age and the incidence of many of these syndromes increases. Improved patient stratification, tight monitoring of disease activity and aspects that influence that (e.g. adherence, smoking) are warranted to improve the outcome of lifelong heterogeneous disorders like Inflammatory Bowel Disease (IBD). However, at present it is not easy to acquire and connect all the necessary data, including patient reported outcome measures, without increasing health care utilisation and costs. 

"The IBD project wants to make use of the DataHub infrastructure in order to combine prospective longitudinal data
from the hospital information systems with patient reported outcomes and experiences.





The IBD project closely collaborates with DataHub in order to make it easy to acquire and connect research data, including patient reported outcome measures, without increasing health care utilisation and costs. The IBD project also wants to make sure that in the near future research data generated by the project comply to the FAIR principles. 

DataHub made it possible to extract data from
the local Electronic Health Records (EHR).
To be able to use the data for other purposes,
for example clinical research or patient
feasibility, the data is exported in a normalised and standardised manner. When a doctor speaks to a patient, the data generated in the EHR will automatically be pseudonymised and converted into the standard format HL7. Of course, this only applies for patients who have given consent to do so. 

The extracted data will be stored for later reuse and retrievability. The data is annotated with terms from the SNOMED CT ontology which enhances the interoperability with other hospitals. The infrastructure is also used to fill the eCRF (Clinical Research Form). With this achievement retyping belongs to the past. 

DataHub Services


  • Highly structured datasets
  • Highly enriched datasets
  • Connected to other datasets


Tools used