I’ve just released a new working paper, along with my co-authors Profs Marilyn James and David Whynes. You can access it through RePEc here. The paper discusses the (somewhat obvious) relationship between a person’s risk of developing a disease and the cost-effectiveness of screening them. This is important because publicly-funded screening interventions will, in the future, I suspect, have to discriminate based on risk.
Here’s the abstract:
Advancements in our understanding of the causes and correlates of disease mean that we are now able to estimate an individual’s level of risk. This, and the ever-increasing need for healthcare interventions to be cost-effective, has led to calls for the introduction of risk-based screening. Risk-based screening would involve the use of information about an individual’s risk factors to decide whether or not they should be eligible for screening, or the frequency with which they should be invited to attend screening. Evidence is emerging that targeted screening, towards those at higher risk, can increase the cost-effectiveness of a screening programme. The relationship between individual risk and the cost-effectiveness of screening an individual is implicitly recognised in current population screening programmes in the UK. However, the nature of this relationship, and its implications for cost-effectiveness analysis, has not been presented in the academic literature. In this study we propose that an individual’s risk of developing a disease has a consistent and quantifiable relationship with the cost-effectiveness of screening them. We suggest a simple modification to standard methods of cost-effectiveness analysis that enables the incorporation of individual risk. Using numerical examples we demonstrate the nature of the relationship between risk and cost-effectiveness and suggest means of optimising a screening intervention. This can be done either by defining a minimum level of risk for eligibility or by defining the optimal recall period for screening. We suggest that methods of decision modelling could enable such an analysis to be carried out, and that information on individual risk could be used to optimise the cost-effectiveness of population screening programmes.
I’d really appreciate any comments you might have on this paper. Feel free to post below or alternatively please send me an email.