Data Driven Decision Support for Clinical Information Systems


There is a large amount of information that is currently amassed in the health care sector, and which is underused in terms of providing relevant clinical information on anything beyond the immediate patient. Utilizing these data has a huge potential for supporting health care workers in providing the best possible care for their patients. Most prominently, the electronic health records (EHRs) of modern hospitals and primary care facilities contain vast and increasing amounts of information that can be used for this purpose.

The project contains three research tracks;

  1. Adverse event identification
  2. Patient similarity and decision aid
  3. Patient pathway analysis


The data information trail generated by a patient moving through the health care system is clearly identifiable and contains valuable clinical information for health care providers and patients. We will use available data from hospital services and statistical and informatics methods to investigate decision support tools.

Project manager

Project participants

External project participants

  • Knut Magne Augestad, NST/UNN
  • Rolv-Ole Lindsetmo, UNN
  • Arthur Revhaug, UNN
  • Mark Girolami, University of Warwick, UK
  • Shahram Ebadollahi, IBM Research, Yorktown Heights, New York, USA


Health data

Project period

2014 - 2017

Last updated

20 January 2020