For innovations to succeed, more is needed than just a successful implementation: they also require accurate, high-quality data. The importance of this requirement is frequently missed. In the Netherlands, for instance, there was an opportunity to create a national database of comparable healthcare data with the introduction of the Electronic Health Record (EHR) in 2011. However, politicians opted not to set down a national standard for the EHR, leaving it to every healthcare institution in the country to implement its own EHR.
As a result, no two EHR's are the same, even if they were made by the same developer. The patient data in different EHR's can therefore neither be compared nor easily combined. Not only that, these data were never recorded with the purpose of being used for Data Science. Which means that the application of Data Science faces several more challenges.

UMC Utrecht’s U-Prevent is a great example of such an innovation, and it has already been applied in the field of cardiovascular risk management. U-Prevent supports physicians and patients in determining cardiovascular risk and gives the physician easy access to a list of available resources and medication that can be used to reduce the risk. As a result, physicians and patients can work together to prevent future problems and disorders that may lead to unnecessary care costs.

In the Netherlands, large sums of public money are invested in healthcare innovation. On the one hand, this is driven by the need to limit further increases in total healthcare costs, whilst on the other hand offering opportunities to improve the quality of patient care. In recent years, attention to the GDPR has slowed down the implementation of innovations. How do you implement and sustainably operate innovations whilst also complying with the GDPR? In the meantime, new insights have led to the development of a more nuanced approach, and innovations that use patient data are prioritized more and more.