Advances in health economic modelling
I have a longstanding interest in methodological developments in health economic modelling. This project collects these and points to any relevant publications.
Markov models are extremely common in economic evaluation, but they have a structural limitation which means it is not possible to know the sojourn time in each state (time spent in that state) and use this to determine the rate of transitions to other states.
A typical workaround is to use tunnel states, but this is not without drawbacks.
I devised a method for calculating expected discounted outcomes when transitions between states are governed by sojourn-dependent time to event distributions. The method uses moment-generating functions and was presented at the Health Economists’ Study Group in Bristol (Summer 2018) and published in Medical Decision Making.
I have submitted a further development in this area to Medical Decision Making, which I presented at the South West Health Economists Meeting 2019.
Probabilistic sensitivity analysis
Probabilistic sensitivity analysis is a way to understand how uncertainty in model parameters translates into uncertainty about what decision to make. It also underpins value of information analyses.
I have submitted an abstract to the SMDM 42nd Annual North American meeting (October 2020) describing a new method for propagating uncertainty through a decision model and conducting probabilistic sensitivity analysis.
- Cost-effectiveness of the Manchester approach to identifying Lynch syndrome in women with endometrial cancer
- A Trial of physical Activity assisted Reduction of Smoking (TARS)
- Economic Analysis of First-Line Treatment with Cetuximab or Panitumumab for RAS Wild-Type Metastatic Colorectal Cancer in England
- COST EFFECTIVENESS OF CETUXIMAB AND PANITUMUMAB FOR FIRST-LINE RAS WT METASTATIC COLORECAL CANCER
- Cost-effectiveness analysis of reflex testing for Lynch syndrome in women with endometrial cancer in the UK setting