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Understanding heterogeneity for patient preference data and how it effects the benefit-risk ratio for treatments

Understanding heterogeneity for patient preference data and how it effects the benefit-risk ratio for treatments

FromThe Effective Statistician - in association with PSI


Understanding heterogeneity for patient preference data and how it effects the benefit-risk ratio for treatments

FromThe Effective Statistician - in association with PSI

ratings:
Length:
54 minutes
Released:
May 27, 2019
Format:
Podcast episode

Description

As statisticians in the medical field, we’re used to study subgroups of patients with respect to all kinds of biological variables: from demographics to genomics. This provides us with a good understanding of how the benefit-risk profile for a given patient looks like.

However, the patient might have a completely different view on the importance of the different benefits and risks. And importantly, these preferences might be less driven by biologic factors and more by personal experiences and situations as well as psychological traits. How can we assess patient preferences in this regard?

Marco Boeri and I worked on such questions in the past and some work has been presented at last years PSI conference. In todays episode, we give you some insights into what’s possible and how you can approach this problem.
Released:
May 27, 2019
Format:
Podcast episode

Titles in the series (100)

The podcast from statisticians for statisticians to have a bigger impact at work. This podcast is set up in association with PSI - Promoting Statistical Insight. This podcast helps you to grow your leadership skills, learn about ongoing discussions in the scientific community, build you knowledge about the health sector and be more efficient at work. This podcast helps statisticians at all levels with and without management experience. It is targeted towards the health, but lots of topics will be important for the wider data scientists community.