Together, we assess and improve your health data quality so you can trust what you learn

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
Together we improve

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.

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

Clinical decisions can be misguided when based on low quality health data. For example, a study found that 48% of patients required additional monitoring, examination or treatment after medication errors resulting from weight errors (Selbst et al., 1999 , Pediatric Emergency Care). Further, cleaning data in preparation of conducting research is time-consuming.

Incomplete or incorrect personal health data can result in erroneous clinical decision support output. In addition, data quality issues in patient subpopulations can yield biased research findings.

Incomplete or incorrect personal health data can result in erroneous clinical decision support output. In addition, data quality issues in patient subpopulations can yield biased research findings.

Our data quality assessment framework

9 data quality dimensions

Designed for patient care, organisational learning and research

Based on scientific literature

Guided by our Data Quality Task Force

Approved by 70 hospital representatives

Our data quality programmes

We support you with two data quality programmes, tailored to your needs.

Data Quality
Champion Programme

We guide you to assess and improve health data quality, to become a data quality champion organisation

Data Quality
Benchmarking Programme

We verify that datasets are fit for purpose and perform sector benchmarking

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 Programme Manager Hannelore Aerts 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

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