Abstract
BACKGROUND:
One of the challenges in economic evaluation of obesity prevention in early childhood is predicting costs and outcomes over a policy relevant time-frame. Existing studies pertain to economic evaluations alongside randomized trials, with a short (generally less than 5 years) time horizon or modelled economic evaluations that mostly take a lifetime horizon and account only for adverse events, costs and quality of life outcomes in adulthood.
OBJECTIVE
To develop a model for cost-effectiveness and cost-utility of early childhood obesity prevention and treatment, that considers a policy relevant time-frame and hence accounts for health outcomes and direct healthcare costs during childhood and adolescence.
DATA AND METHODS:
We use individual–level (micro-simulation) modelling to project BMI, prevalence of overweight and obesity, QALYs and direct healthcare costs from early childhood to adolescence (4 to 15 years). The modeling of BMI trajectories is informed by Australian population representative data on children, the Longitudinal Study of Australian Children (LSAC). The model also incorporates data from systematic reviews and other published literature relating to the association of quality of life and direct health care costs with weight status. The EPOCH model has been designed as a ‘multi-use’ model and can project outcomes in terms of BMI/BMI-z units saved, or QALYs gained. In this presentation, we describe the model, present internal and external validation, and demonstrate use of the model for cost-utility and cost-effectiveness analysis. Examples will be given of running on individual level data from early intervention trials (using outcome data at 4 years), and running on population level Australian data, onto which intervention effects are overlaid through effects on BMI. We also demonstrate examples of modelling multiple interventions during childhood, and modelling highly targeted interventions.
RESULTS AND CONCLUSIONS:
The model showed good validation over a 10-year period. Projection of BMI throughout childhood and adolescence corresponded well to observed national data, giving confidence in model projections For example, starting with an input population of 4 and 5 year-olds from LSAC, simulated mean BMI at age 14/15 years was 22.4 kg/m2 (95% CI 22.2 – 22.5) compared with 22.2 kg/m2 units (95% CI 22.0 –22.3) observed in survey data. The model also projects the increasing right skew in the distribution of body mass index (BMI) in the modelled populations, and prevalence of weight status consistent with observed data. It is hoped the EPOCH model will be able to compare obesity interventions or combinations of interventions during childhood and will be useful for priority setting. The strengths of the model are: it is conceptually simple, has been validated prior to using for economic evaluation, and has simple requirements to run using trial data (age, sex, BMI and socio-economic status). Additionally, it accounts for individual heterogeneity and the full population distribution of body mass index (BMI) in the modelled populations, and as such, predicted outcomes are not restricted to healthy, overweight and obese categories. A disadvantage is that the model is implemented in STATA and hence is more demanding in terms of software/coding skills than some other modelling platforms.
One of the challenges in economic evaluation of obesity prevention in early childhood is predicting costs and outcomes over a policy relevant time-frame. Existing studies pertain to economic evaluations alongside randomized trials, with a short (generally less than 5 years) time horizon or modelled economic evaluations that mostly take a lifetime horizon and account only for adverse events, costs and quality of life outcomes in adulthood.
OBJECTIVE
To develop a model for cost-effectiveness and cost-utility of early childhood obesity prevention and treatment, that considers a policy relevant time-frame and hence accounts for health outcomes and direct healthcare costs during childhood and adolescence.
DATA AND METHODS:
We use individual–level (micro-simulation) modelling to project BMI, prevalence of overweight and obesity, QALYs and direct healthcare costs from early childhood to adolescence (4 to 15 years). The modeling of BMI trajectories is informed by Australian population representative data on children, the Longitudinal Study of Australian Children (LSAC). The model also incorporates data from systematic reviews and other published literature relating to the association of quality of life and direct health care costs with weight status. The EPOCH model has been designed as a ‘multi-use’ model and can project outcomes in terms of BMI/BMI-z units saved, or QALYs gained. In this presentation, we describe the model, present internal and external validation, and demonstrate use of the model for cost-utility and cost-effectiveness analysis. Examples will be given of running on individual level data from early intervention trials (using outcome data at 4 years), and running on population level Australian data, onto which intervention effects are overlaid through effects on BMI. We also demonstrate examples of modelling multiple interventions during childhood, and modelling highly targeted interventions.
RESULTS AND CONCLUSIONS:
The model showed good validation over a 10-year period. Projection of BMI throughout childhood and adolescence corresponded well to observed national data, giving confidence in model projections For example, starting with an input population of 4 and 5 year-olds from LSAC, simulated mean BMI at age 14/15 years was 22.4 kg/m2 (95% CI 22.2 – 22.5) compared with 22.2 kg/m2 units (95% CI 22.0 –22.3) observed in survey data. The model also projects the increasing right skew in the distribution of body mass index (BMI) in the modelled populations, and prevalence of weight status consistent with observed data. It is hoped the EPOCH model will be able to compare obesity interventions or combinations of interventions during childhood and will be useful for priority setting. The strengths of the model are: it is conceptually simple, has been validated prior to using for economic evaluation, and has simple requirements to run using trial data (age, sex, BMI and socio-economic status). Additionally, it accounts for individual heterogeneity and the full population distribution of body mass index (BMI) in the modelled populations, and as such, predicted outcomes are not restricted to healthy, overweight and obese categories. A disadvantage is that the model is implemented in STATA and hence is more demanding in terms of software/coding skills than some other modelling platforms.
Original language | English |
---|---|
Publication status | Published - 15 Jul 2019 |
Event | iHEA World Congress on Health Economics 2019 - Basel, Switzerland Duration: 13 Jul 2019 → 17 Jul 2019 https://healtheconomics.org/congress/ https://www.healtheconomics.org/wp-content/uploads/2022/07/2019-abstract_book.pdf |
Conference
Conference | iHEA World Congress on Health Economics 2019 |
---|---|
Abbreviated title | iHEA 2019 |
Country/Territory | Switzerland |
City | Basel |
Period | 13/07/19 → 17/07/19 |
Internet address |