Data-Enabled Policy Making in Healthcare

Guest Blog Post by Maritta Perälä-Heape, PhD; Director, Centre for Health and Technology (CHT), University of Oulu

The availability of an ever-increasing amount of data is a resource whose value is impossible to imagine.

Data plays roles in gaining competitive advantage, optimisation of resources, cost reduction, value creation, accuracy and accountability, and in hedging uncertainty. Data brings efficiency and effectiveness to the strategic policy decision-making processes. The value of data lies in the predictions that it enables. We will be able to analyse large and complex data sets to identify trends and provide valuable insights that can inform strategic decisions about future service or workforce needs. The ability to automate the processing and analysis of huge amounts of data provides a strong advantage over the sole reliance on human resources and also makes it possible to use several data sets simultaneously.

But, do we really understand the power of the data, and its potential as a resource to support smarter policy decision-making? In many organisations, data is collected to analyse cost-effectiveness and the customer satisfaction of services. The way we are collecting, storing and sharing the data is old-fashioned and does not reflect the needs and opportunities it could raise in the future. We should avoid the temptation to systematically prioritise technology development over efforts to define data management strategies.

Current data collection practices, as well as the data sets themselves that have been used for earlier purposes, differ from those needed for predicting future health problems and the needs for new service offerings. We need to understand the predictive value of data and reflect on the possibilities of the data that we have not yet collected.

The management in organisations should attach a lot of importance to data sourcing, analysis, interpretation and exploitation in order to create competitive advantage. There is increasing demand to make the data actionable in the real-life situations. For such situations, where data is a key resource, it is imperative that we enhance its security.

More research is needed on the potential of data to overcome the above-mentioned challenges. In a world where the mass of disconnected data is continually growing, it is imperative that we develop a strategy for its management. While doing this, it is essential to bear in mind that policy-makers and clinicians are not always experts in data analysis.

There are numerous ongoing R&D projects at the European level. Many R&D projects are initiated without knowing, or understanding, the current regulations governing data-sharing, or about the ownership of data.

Every health data-related project should share the best practices on data sharing. This is important when anonymised health data is used for scientific purposes or international health initiatives. These actions should influence the activities on the regulation on electronic data sharing, data protection, privacy across borders and data format standardisation.

In the H2020-funded MIDAS (Meaningful Integration of Data Analytics and Services) project, we are evaluating how different data sources, including personal data, can be integrated and exploited in healthcare policy-making.

The MIDAS project is increasing the awareness of data sharing principles, supporting the EU single market strategies, and influences the policies made in the context of the digital transition in the EU Urban agenda (Future Health).