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1.
Mhealth ; 9: 12, 2023.
Article in English | MEDLINE | ID: mdl-37089273

ABSTRACT

Background: The rising prevalence of type 2 diabetes in Australia is a public health concern, contributing to significant disease burden and economic costs. Text-message programs have been shown to improve health outcomes for people with type 2 diabetes, however they remain underutilized, and no evidence exists on their cost-effectiveness or costs of scale up to a population level in Australia. This study aimed to determine the cost-effectiveness and cost-utility of a 6-month text-message intervention (DTEXT) to improve glycated hemoglobin (HbA1c) and self-management behaviors for Australian adults with type 2 diabetes. Methods: A within-trial economic evaluation was conducted on the DTEXT randomized controlled trial. Incremental cost-effectiveness ratios (ICERs) were determined per 11 mmol/mol (1%) reduced HbA1c and per quality adjusted life year (QALY) gained, compared to usual care. Cost-effectiveness acceptability curves (CEAC) determined the probability of the intervention being cost-effective over a range of willingness to pay thresholds. A scenario analysis was conducted to determine how cost-effectiveness was impacted by using current implementation costs. Results: The DTEXT intervention cost AU$36 (INT$24) per participant, with an ICER of AU$311 (INT$211) per 11 mmol/mol (1%) reduced HbA1c. Based on HbA1c outcomes, DTEXT had a 33% probability of being effective and cost-saving. Based on the QALY outcomes, the intervention had only a 24% probability of being cost-effective. Scenario analysis indicated costs per participant of AU$13 (INT$9) to deliver the intervention, with a reduced incremental cost effectiveness ratio of AU$151 (INT$103) per 11 mmol/mol (1%) reduced HbA1c and a 38% probability of being effective and cost-saving. Conclusions: DTEXT was low cost and potentially scalable, but only had a low to moderate probability of being effective and cost saving. Further research should determine more targeted approaches that may improve cost-effectiveness. Trial Registration: ACTRN12617000416392.

2.
Pediatr Obes ; 15(12): e12684, 2020 12.
Article in English | MEDLINE | ID: mdl-32558343

ABSTRACT

BACKGROUND: In the absence of rigorous evidence of cost-effectiveness for early childhood obesity prevention interventions, the next-best option may be for decision-makers to consider the relevant costs of interventions when allocating resources. OBJECTIVES: This study aimed to estimate systematically the cost of five obesity prevention interventions in children aged 0-2 years, undertaken in research settings in Australia and New Zealand. METHODS: A standardised costing protocol informed the costing methodology, ensuring comparability of results across interventions. Micro-costing was undertaken, with intervention costs defined from the funder perspective and valued in 2018 Australian dollars using unit costs from the trials or market rates. RESULTS: Interventions varied widely in their resource use. The total cost per participant ranged from $80 for the CHAT SMS intervention arm (95% UI $77-$82) to $1135 for the Healthy Beginnings intervention (95% UI $1059-$1189). Time costs of personnel delivering interventions contributed >50% of total intervention costs for all included studies. CONCLUSIONS: An understanding of the costs associated with intervention delivery modes is important, alongside effectiveness. Telephone delivery may include unexpected costs associated with connection to intervention participants at convenient times. A SMS-based intervention had the lowest delivery cost in this study.


Subject(s)
Pediatric Obesity/prevention & control , Australia , Child, Preschool , Cost-Benefit Analysis , Costs and Cost Analysis , Female , Humans , Infant , Infant, Newborn , Male
3.
Article in English | MEDLINE | ID: mdl-30881347

ABSTRACT

Background: Childhood obesity is a serious public health issue. In Australia, 1 in 4 children is already affected by overweight or obesity at the time of school entry. Governments around the world have recognized this problem through investment in the prevention of pediatric obesity, yet few interventions in early childhood have been subjected to economic evaluation. Information on cost-effectiveness is vital to decisions about program implementation. A challenge in evaluating preventive interventions in early childhood is to capture long-term costs and outcomes beyond the duration of an intervention, as the benefits of early obesity prevention will not be realized until some years into the future. However, decisions need to be made in the present, and modeling is one way to inform such decisions. Objective: To describe the conceptual structure of a new health economic model (the Early Prevention of Obesity in CHildhood (EPOCH) model) for evaluating childhood obesity interventions; and to validate the epidemiologic predictions. Methods and Results: We use an individual-level (micro-simulation) method to model BMI trajectories and the progression of obesity from early childhood to adolescence. The equations predicting individual BMI change underpinning our model were derived from data from the population-representative study, the Longitudinal Study of Australian Children (LSAC). Our approach is novel because it will account for costs and benefits accrued throughout childhood and adolescence. As a first step to validate the epidemiological predictions of the model, we used input data representing over 250,000 children aged 4/5 years, and simulated BMI and obesity trajectories until adolescence. Simulated mean BMI and obesity prevalence for boys and girls were verified by nationally-representative data on children at 14/15 years of age. Discussion: The EPOCH model is epidemiologically sound in its prediction of both BMI trajectories and prevalence of obesity for boys and girls. Future developments of the model will include socio-economic position and will incorporate the impacts of obesity on healthcare costs. The EPOCH model will help answer: when is it best to intervene in childhood; what are the most cost-effective approaches and which population groups will benefit most from interventions.

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