Multi-party computation: optimising care by encrypting patient data

Go straight to information on:

• Personalized health care interventions
  
• How can MPC improve cancer treatment?
  
• In practice: Optimising HIV treatment with MPC
  
• In practice: Care for Data app
  
• In practice: MPC for financial institutions and the government

Personalized health care interventions

In July 2020, in collaboration with Erasmus MC, Zilveren Kruis and ZorgTTP, TNO demonstrated that it is possible to securely link and analyze personal data from multiple organizations. By using state-of-the-art cryptography, a pilot with synthetic data demonstrated that these types of solutions work in practice. Insurance data can be combined with hospital data in the future to make better predictions about diseases and conditions, such as for heart failure. And those predictions can be used by doctors for personalized health care interventions.

• Read more: Identifying heart failure patients at high risk using MPC - Marie Beth van Egmond

Collaboration with oncology

TNO and the Netherlands Comprehensive Cancer Organisation (IKNL) are working together to generate insights from the ever-increasing amounts of data available from cancer patients. This can ultimately help to reduce the impact of cancer by increasing the chances of recovery and preventing cancer in the first place. Within this multidisciplinary collaboration – between doctors, epidemiologists, data scientists and clinical computer scientists, among others – MPC is used to extract more value from the available data of the Netherlands Cancer Registry (NCR) and other sources. The NCR contains data on diseases, care and outcomes.

The ambition of TNO and IKNL for 2020 is to develop privacy-secure, open-source software. This software will be more widely applicable in many more healthcare applications. In this way, these new innovations can be of maximum benefit to the patient.

The search for optimal hiv treatment

HIV research also runs into problems regarding the use of privacy-sensitive patient data. MPC technology can offer a solution in this area too. TNO, together with research groups at the University of Amsterdam (UvA) and Centrum Wiskunde & Informatica (CWI), has conducted research into the suitability of MPC when it comes to determining the optimal treatment for an individual HIV patient without compromising privacy.All those involved are enthusiastic and think that MPC can also be used to determine the best treatment for other diseases and within other sectors.

Care for Data

Platform for secure data analysis in care

The Care for Data platform was developed in collaboration with CZ, Zuyderland Hospital and CBS. This decentralised platform makes it possible to perform statistical analyses of care data that remain with different parties in a secure manner and of which only the results for the total population are visible (data on a personal level is therefore never shared). Additionally, no Trusted Third Party is needed to anonymise the data.

Care for Data is a scalable platform which makes it possible to continuously assess the effectiveness of care innovations at a low cost or to monitor the quality of care (value-based healthcare) without sensitive data ending up with other parties. TNO is looking for parties that want to evaluate the cost-effectiveness of an existing healthcare innovation or that are interested in monitoring value-based healthcare contracts.

MPC for financial institutions and the government

It isn’t just healthcare that benefits from MPC’s unique ability to combine and share data without revealing the content. Through collaboration – read, combining their datasets – financial institutions will also be better able to detect fraud and money laundering activities, for example. Here too, the data that make this possible are sensitive and should not be shared unnecessarily. MPC can improve fraud detection by securely connecting the data.

MPC can also benefit the various governmental parties that work together to trace fugitives who have yet to serve their custodial sentences. Thanks to MPC, parties within the chain of investigation can use one another’s data without sharing sensitive personal data unnecessarily. Want to know how? Download the PDF.