Department for Health Data Analytics
We are looking at how health data can be used to predict, detect and treat disease. Machine learning algorithms and data mining methods are some of the things we are studying. We will develop methods for analysing data and protecting privacy. A central topic is how the health sector can make use of reliable and sustainable algorithms.
Better use of health data
A national aim is to improve the access to health data for quality improvement, health monitoring, and control management and research. Privacy preserving of patient information is required for maintaining trust from patients and healthcare professionals. Advanced statistical methods shall be developed to retrieve useful and meaningful information from large volumes of data.
Patient data are generated in health care systems. Access to data and the tremendous growth in computer processing power makes it possible to use new methods in analytics. It gives decision-makers, health workers and citizens new tools. Advanced analytics enable health professionals to predict, diagnose and treat disease. Health data analysis is an evolving and complex field with many different stakeholders.
- Making data from electronic health records available and do secondary studies
- See EPR data and data from other sources in context
- Computerized clinical decision support for doctors
- Safeguard patients’ privacy
- Knowledge about ICT systems that collect data from different sources
- Secondary analyses, using pattern recognition, visualising, predictive modelling, time series analysis, textual analysis and more