
Health data quality,
a dynamic complexity
Good data provides the right insights. Be prepared for new opportunities!
- Deliver safe, personalised and evidence-based patient care
- Optimise care coordination and care pathways
- Embrace value-based health care
- Participate in clinical studies, accelerate new medical advances and open up new revenue streams

Minor errors, major implications
Ensuring high-quality data seems evident and straightforward, but unfortunately this is not the case in practice. Several studies have demonstrated that routinely collected health data today is of variable quality, and is often not fit for the intended purpose.

The annual financial impact of poor data quality on organisations is estimated to lie between $9.7 million and $3.1 trillion (Gartner & IBM).
Our data quality assessment framework

9 data quality dimensions

Designed for patient care, organisational learning and research

For health data providers, users and supporters

Based on scientific literature

Guided by our Data Quality Task Force

Approved by 70 hospital representatives
Together, we scale up your health data quality so you can trust what you learn
Interested? Get in touch!
Are you interested to learn more about data quality? Would you like more information regarding a data quality assessment?
Contact our Data Quality Manager Jens Declerck for a free intake meeting.
(1) Hirata, K. M., Kang, A. H., Ramirez, G. V., Kimata, C., & Yamamoto, L. G. (2019). Pediatric Weight Errors and Resultant Medication Dosing Errors in the Emergency Department. Pediatric Emergency Care, 35(9), 637–642.
https://doi.org/10.1097/PEC.0000000000001277
(2) Selbst, S. M., Fein, J. A., Osterhoudt, K., & Ho, W. (1999). Medication errors
in a pediatric emergency department. Pediatric Emergency Care, 15(1), 1–4.
https://doi.org/10.1097/00006565-199902000-00001