Disputas Per Olav Løvsletten

Tittel på avhandling er Evaluation and refinement of an interactive decision support tool displaying structured evidence summaries from network meta-analysis

Tid: 21. nov kl. 13:15

Sted: Rikke Nissen auditorium, Lovisenberg Diakonale Sykehus, Lovisenberggata 21.

Prøveforelesningen med tittelen, Uncertainty tolerance and its effect on decision-making in clinical practice samme sted kl. 10:15

Abstract

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.