What is the economic evidence for mHealth? A systematic review of economic evaluations of mHealth solutions

Background Mobile health (mHealth) is often reputed to be cost-effective or cost-saving. Despite optimism, the strength of the evidence supporting this assertion has been limited. In this systematic review the body of evidence related to economic evaluations of mHealth interventions is assessed and summarized. Methods Seven electronic bibliographic databases, grey literature, and relevant references were searched. Eligibility criteria included original articles, comparison of costs and consequences of interventions (one categorized as a primary mHealth intervention or mHealth intervention as a component of other interventions), health and economic outcomes and published in English. Full economic evaluations were appraised using the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) checklist and The PRISMA guidelines were followed. Results Searches identified 5902 results, of which 318 were examined at full text, and 39 were included in this review. The 39 studies spanned 19 countries, most of which were conducted in upper and upper-middle income countries (34, 87.2%). Primary mHealth interventions (35, 89.7%), behavior change communication type interventions (e.g., improve attendance rates, medication adherence) (27, 69.2%), and short messaging system (SMS) as the mHealth function (e.g., used to send reminders, information, provide support, conduct surveys or collect data) (22, 56.4%) were most frequent; the most frequent disease or condition focuses were outpatient clinic attendance, cardiovascular disease, and diabetes. The average percent of CHEERS checklist items reported was 79.6% (range 47.62–100, STD 14.18) and the top quartile reported 91.3–100%. In 29 studies (74.3%), researchers reported that the mHealth intervention was cost-effective, economically beneficial, or cost saving at base case. Conclusions Findings highlight a growing body of economic evidence for mHealth interventions. Although all studies included a comparison of intervention effectiveness of a health-related outcome and reported economic data, many did not report all recommended economic outcome items and were lacking in comprehensive analysis. The identified economic evaluations varied by disease or condition focus, economic outcome measurements, perspectives, and were distributed unevenly geographically, limiting formal meta-analysis. Further research is needed in low and low-middle income countries and to understand the impact of different mHealth types. Following established economic reporting guidelines will improve this body of research

Estimating the impact of school-based education and restriction on television advertising to prevent childhood obesity in Thailand

INTRODUCTION: The prevalence of overweight in children aged 6–14 years in Thailand has significantly increased, doubling from 5.8% to 13.9% between 1995 and 2014. The aim of this study was to estimate how many cases of childhood overweight and obesity could be prevented by implementing school-based education programs and restriction on television (TV) advertising. MATERIALS AND METHODS: A mathematical model was developed to estimate the impact of two interventions: a school-based education program to reduce consumption of carbonated drinks and restriction of unhealthy food and beverages advertising on TV. Sex-specific body mass index (BMI) for Thai children aged 6–12 years were calculated using weight and height data from the National Health Examination Survey Round V in 2014. We used a lognormal distribution to fit the BMI data and modelled a shift in the distribution to quantify the impact of the interventions. The prevalence of overweight and obesity was then estimated by age and sex using BMI cut-offs from the International Obesity Task Force. For the school-based education intervention, the mean BMI reduction 0.1 kg/m2 in children was adopted from an English cluster randomized controlled trial. For the intervention restricting TV advertising of unhealthy food and beverages high in fat, sugar and salt (HFSS), the mean BMI reduction was calculated from change in energy intake (in Kilocalories) per minute exposed to these advertisements, followed by change in weight and then BMI. This required the following data: (1) minutes per day that Thai children spent watching HFSS food advertisements, (2) kilocalorie effect per minute exposed to TV advertisements from meta-analysis, and (3) adjustment for real world and mealtime compensation. RESULTS: Restricting TV advertising of unhealthy food and beverages reduced BMI on average by 0.32 kg/m2. The school-based education intervention was estimated to reduce overall prevalence of childhood overweight and obesity by 3.5% (3.2% in male, 3.8% in female), lowering the number of cases with overweight and obesity from 1.10 million to 1.06 million. Restriction on TV advertising reduced overall prevalence of childhood overweight and obesity by 11% (10.0% in male, 12.3% in female), lowering the number of cases with overweight and obesity from 1.10 million to 0.98 million. CONCLUSION: Both interventions were estimated to significantly reduce childhood overweight and obesity in Thailand, although restricting TV advertising of unhealthy food and beverages could have a much bigger impact. Intervention effects alone are insufficient for decision-making. Hence, cost-effectiveness analysis is needed to inform policy makers on the allocation of limited resources for childhood obesity prevention in Thailand. DISCLOSURE OF INTEREST: P. Hunchangsith Grant/Research support with: Thai Health Foundation, L. Aminde: None declared, L. Veerman: None declared, W. Ngam-a-roon: None declared.No Full Tex