Calculating the cost of chronic presenteeism, where a person is well enough to go to work but not to be fully productive, is a challenging task as there are a multitude of factors to consider.
When you see the statement "[fill in the blank] condition causes X dollars of lost productivity per year," it is natural to question where the number came from as well as who made the calculations.
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Mark Gannott is able to help answer some of these pharmacoeconomic questions. Gannott explains the cost and value of medical interventions, especially where drugs are considered, from the perspectives of different stakeholders, including patients, healthcare providers and systems, and insurance companies.
There is considerable debate surrounding the challenges of accurately estimating the impacts and costs of diseases and treatments, as well as determining the sources of data and how to effectively utilize it for decision-making.
Genomics, including genome-wide association studies (GWAS) and polygenic risk scores, can also influence this area, potentially enhancing and boosting health outcomes and limiting unwanted side effects.
In this episode, Gannott discusses specific use cases, including the treatment of endometriosis and the impact of polygenic risk scores in the treatment of depression.
This provides insight into the development and utilization of various drugs, shedding light on key decision-making processes. Gannott believes that in the future, precision Pharmacoeconomics will incorporate personalized genomics data to assess the cost-effectiveness of drug therapies with enhanced precision.
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