A ′microsimulation′ model for assessing the cost effectiveness of physical activity interventions

Background: Methods used to consider whether physical activity interventions offer value for money rarely account for characteristics that influence the uptake and sustainability of physical activity (PA) (e.g. age, gender, health status). As individuals can opt in or out of interventions easily, it is important to reflect the diversity in a population to maximise the efficiency gainable from PA interventions. This study explores which points in the life course, of inactive people, it is cost-effective to intervene to increase and maintain PA. Methods: An individual-level simulation model is used to model the cost-effectiveness and budget impact of PA interventions (exercise referral scheme (ERS) as an exemplar). The model allows individuals’ to experience events (e.g. uptake of PA intervention, onset of heart disease, diabetes, depression) at times in their lifetime that are influenced by their characteristics and activity levels. Data used to populate the model parameters were derived from best evidence reviews. Results: Cost-effectiveness of ERS is summarised as incremental cost per quality adjusted life year and net benefit statistics. The cases of CVD/diabetes/depression avoided; and budget impact of ERS is also reported. Costs are presented separately, for different funders (e.g. health care providers and local authorities) and broken down into three categories: programme-level costs of ERS; patient-level costs of ERS; and savings from avoided treatment. The uncertainty around results is presented using the cost effectiveness: plane and acceptability curve. Conclusions: The model informs policy at national and local levels in selecting or promoting efficient ways of increasing PA among different groups of people and at different stages of the life course. Discussion focuses on extending the model to other sectors and countries. Main message: An innovative individual level simulation approach to model the cost effectiveness and budget impact of PA interventions