Due to copyright issues, an electronic copy of the thesis must be ordered from the faculty. For the faculty to have time to process the order, the order must be received by the faculty at the latest 2 days before the public defence. Orders received later than 2 days before the defence will not be processed. After the public defence, please address any inquiries regarding the thesis to the candidate.
Trial Lecture – time and place
See Trial Lecture.
Adjudication committee
- First opponent: Associate professor Huseyin Naci, London School of Economics and Political Science (LSE),
- Second opponent: Professor Andrea Cipriani, University of Oxford,
- Third member and chair of the evaluation committee: Professor Pål Gulbrandsen, University of Oslo
Chair of the Defence
Associate professor Hanne Cathrine Lie, University of Oslo
Principal Supervisor
Professor Per Olav Vandvik, University of Oslo
Summary
With a fast-growing number of available treatment options, it is becoming increasingly challenging for clinicians, patients, and policymakers to identify which interventions strike the best balance between effectiveness and safety. To address this challenge, Per Olav Løvsletten and colleagues have developed MATCH-IT, an interactive decision support tool.
In his doctoral thesis — Evaluation and refinement of an interactive decision support tool displaying structured evidence summaries from network meta-analysis — Løvsletten and his collaborators explored how findings from network meta-analysis in systematic reviews can be presented in a clearer and more accessible way. The aim was to improve how complex research results are communicated to support more informed medical decision-making.
MATCH-IT was refined and tested in collaboration with physicians from Norway, Belgium, and Canada, as well as international multidisciplinary guideline panels. Across countries and professional groups, participants found the tool both informative and user-friendly. The use of colour coding was particularly appreciated, as it made it easier to assess which treatments are likely to be most effective and least harmful.
Decision support tools like MATCH-IT — capable of comparing multiple treatments simultaneously — are still scarce internationally. A systematic mapping conducted by the researchers showed that similar visual summaries were available in only 1.5 percent of large systematic reviews analysed.
The researchers conclude that MATCH-IT may help improve understanding of the evidence underlying medical decisions, both at the individual and system level. However, further research is needed to explore how the tool can best be implemented in real-world decision-making settings involving patients.
Additional information
Contact the research support staff.