Health data is sensitive information. Thus, it is justified that the law defines precisely how the data is used.
“In a scientific sense, however, the strict regulation is a challenge as it slows down the development of data-based solutions. For example, in order to transfer data for analyses, many kinds of agreements are needed”, says research team leader Mika Hilvo from VTT, Technical Research Centre of Finland, who coordinates the project in Finland.
The international Secure-e-Health project develops new methods for secure processing of fragmented health data. This lays the groundwork for the development of health-promoting services, where data are used in disease risk prediction and clinical decision-making, for example. EU-level regulation (Medical Devices Regulation, MDR) must be taken into account in the development of medical devices, such as information systems.
Federated learning and data harmonization play a key role
Data fragmentation refers to both the different locations of the data and the methods used to collect it. Federated learning, i.e. local processing of data, solves the challenges associated with transferring data. The health data itself is not transferred, but instead parameters are calculated from it, and they can be transferred securely. These parameters can be used, for example, to create predictive models that support doctors in decision-making.
Health data is collected, for example, by home monitoring methods and in various patient information systems. Information obtained from different data sources must be harmonized before it can be used in risk prediction. New, standardised data models provide means for this.
“The aging of the population is a Europe-wide challenge that we can respond to by designing humane, preventive services that support, for example, living at home as an elderly. Data-driven development also helps to target services correctly. Solita Health has developed, for example, a Kotidigi home monitoring system, and an artificial intelligence tool, Oravizio, for risk assessment for orthopaedics. In addition, we have developed a RegProof™ operating model that utilizes modern designing, software development methods, but also helps take into account the legislation and regulations regarding medical devices, such as medical devices as software”, commented Risto Kaikkonen, Director of Solita Health. Solita has been awarded the international ISO 13485 quality certificate for the design and production of healthcare equipment and supplies.
In order to protect health data, effective identity and user management is also needed to limit access to data precisely. In addition, we need new encryption methods and algorithms that guarantee data security even in the era of quantum computers. These methods are also being developed in the project.
Application area: risk predictions of cardiovascular diseases
The new methods will first be applied to cardiovascular disease risk predictions. Together with its company partners, VTT is investigating how the condition and rehabilitation of a person suffering from heart problems can be predicted using health data.
The heart patient’s condition is monitored at home using Bittium’s wearable device and Solita’s home monitoring system. This data is combined with the data obtained from Mediconsult’s patient information systems and to official register data acquired by Success Clinic. CSIT is responsible for health data security and access control. VTT is developing a machine learning model that predicts risks based on data. Nordic Healthcare Group is investigating how the new methods can be integrated into the patient’s treatment path. Success Clinic develops methods to model the changes in medication use. Eventually, the aim is to incorporate the new machine-learning models into patient information systems.
Large-scale health benefits and global business
There are great expectations related to health data, machine learning, and artificial intelligence. With the help of new methods, these promises can now be redeemed by improving the prediction of risks and the identification of patients at risk. This can facilitate decision-making and the allocation of healthcare resources, as well as produce public health benefits and have a broad impact on people’s well-being even before getting sick.
“Finland and the Nordics are at the forefront of research of the new methods: we have unique health data reserves and top-class expertise in developing these innovations. Solutions based on health data have enormous potential in the international market. Finland has good opportunities to be in the front line of this development also globally,” states Hilvo.
The Secur-e-Health project started on January 1, 2023 and will last for three years. Five countries (Finland, Germany, Canada, Netherlands, Portugal) participate in the project. VTT coordinates the Finnish country consortium, which includes six companies (Bittium, CSIT Finland, Mediconsult, Nordic Healthcare Group, Solita and Success Clinic). In Finland, the project is financed by Business Finland.
For more information
VTT, Mika Hilvo, PhD, Research Team Leader, Health Data Analytics, +358 50 5347782, [email protected]
Solita, Risto Kaikkonen, Director, Health and Wellbeing, +358 41 536 8745, [email protected]
Solita, Manu Setälä, Head of Research, +358 50 557 7910, [email protected]