Accounting for capacity constraints in economic evaluations of stratified medicines: an application in lung cancer                 

Year of award: 2016


  • Stuart Wright

    University of Manchester

Project summary

National decision makers analyse the cost-effectiveness of healthcare interventions to inform whether they should be introduced. I will combine methods from mathematical programming with decision-analytic modelling to identify the effect of capacity constraints on the relative cost-effectiveness of stratified medicines for the treatment of lung cancer in the NHS. I will identify the impact of different constraints in terms of the benefits to patients achieved and the cost of stratified medicine, and find areas for improvement.

Failing to account for capacity constraints in cost-effectiveness analysis of stratified medicine interventions may give a false impression about relative costs and benefits. Omitting capacity constraints may lead to interventions being adopted when they do not provide the promised health benefits. Failing to account for capacity constraints may give the impression that apparently cost-effective interventions can be quickly adopted into clinical practice when investment must be made to support these treatments. This may lead to heterogeneity in provision of stratifying interventions leading to inequality in treatment options.