News Alert:

Decision Support Tool for Alzheimer’s Disease – University of Cambridge

1st April 2022

Innovators from the Department of Clinical Neurosciences at the University of Cambridge had developed a machine learning algorithm to predict the speed of progression of Alzheimer’s disease. This decision support tool would enable physicians to better manage their patients by assigning them to the most appropriate treatment pathway. The innovators wanted to get a better grasp of the health economic benefits provided by their technology and needed a health economic assessment to support further funding rounds.

Our Approach

Health Tech Enterprise (HTE) conducted a literature review and built a fully interactive model to simulate the budgetary impact of the technology on the addressable patient population over a time period of 5 years, as well as over the lifetime of an average patient in the UK.

The Outcome

The Budget Impact Analysis forecast a substantial potential saving cumulated over a period of 5 years. The sensitivity analysis revealed which of the benefits has the biggest potential budgetary impact, and recommendations were formulated as to what data would need to be verified and validated in future studies.

“The budget impact analysis has given fresh insights into our market penetration plans, as well as helping to secure additional funding for the project. HTE has been a pleasure to work with as a partner in this project – they have taken the time to make sure the assessment is tailored to our needs and as accurate as possible for the project.” Dr Timothy Rittman, Co-founder

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