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Stud Health Technol Inform. 2019 Aug 21;264:373-377. doi: 10.3233/SHTI190246.

A Privacy-Preserving Infrastructure for Analyzing Personal Health Data in a Vertically Partitioned Scenario.

Author information

1
Institute of Data Science, Maastricht University, Maastricht, The Netherlands.
2
Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University, Medical Centre+, Maastricht, The Netherlands.
3
Statistics Netherlands (Centraal Bureau voor de Statistiek), Heerlen, The Netherlands.
4
Department of Social Medicine, CAPHRI Care and Public Health Research Institute, Maastricht University, The Netherlands.
5
Department of Internal Medicine, CARIM School for Cardiovascular Diseases, Maastricht University, Maastricht, The Netherlands.
6
Department of Health, Ethics and Society, CAPHRI Research School, Maastricht University, Maastricht, The Netherlands.

Abstract

It is widely anticipated that the use and analysis of health-related big data will enable further understanding and improvements in human health and wellbeing. Here, we propose an innovative infrastructure, which supports secure and privacy-preserving analysis of personal health data from multiple providers with different governance policies. Our objective is to use this infrastructure to explore the relation between Type 2 Diabetes Mellitus status and healthcare costs. Our approach involves the use of distributed machine learning to analyze vertically partitioned data from the Maastricht Study, a prospective population-based cohort study, and data from the official statistics agency of the Netherlands, Statistics Netherlands (Centraal Bureau voor de Statistiek; CBS). This project seeks an optimal solution accounting for scientific, technical, and ethical/legal challenges. We describe these challenges, our progress towards addressing them in a practical use case, and a simulation experiment.

KEYWORDS:

Data Science; Health Information Systems; Machine Learning

PMID:
31437948
DOI:
10.3233/SHTI190246
[Indexed for MEDLINE]

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