Predicting the real-world effectiveness and safety of medical interventions
The aim of this project is to develop new methods for personalizing the choice of treatment, based on the individual characteristics, needs and preferences of patients in every-day clinical practice. Our methods will employ evidence from multiple randomized clinical trials, as well as data collected under real-world clinical conditions.
The specific objectives are (i) to develop and test a range of methods for making patient-specific predictions about the effects of medical interventions and (ii) to develop easy-to-use online software tools that will utilize all developed methods in order to enhance the decision-making process in every-day clinical settings.
This work aims to help clinical practice move away from the one-size-fits-all approach to treating patients, by using evidence-based methods to choose the best treatment for each particular patient. The output of this project is expected to be of importance to research scientists and methodologists, but also to health-care professionals, patients, guideline developers and the pharmaceutical industry.
This project has received funding from the Swiss National Science foundation (SNF), grant 180083 (Principal Investigator Orestis Efthimiou).
Links to web applications developed for the aims of this project
- Web app for personalizing the choice between guided and unguided Cognitive Behavioral Therapy (CBT) for patients with depression, available in
- Web app for personalizing the choice of pharmacological treatment for patients in major depression, available in
- Example web app for personalizing the choice of treatment in a network meta-analysis of multiple outcomes, available in