Cost-effectiveness of a mobile technology-enabled primary care intervention for cardiovascular disease risk management in rural Indonesia

Abstract

Abstract Cardiovascular diseases (CVD) are the leading cause of death in Indonesia, and there are large disparities in access to recommended preventative treatments across the country, particularly in rural areas. Technology-enabled screening and management led by community health workers have been shown to be effective in better managing those at high risk of CVD in a rural Indonesian population; however, the economic impacts of implementing such an intervention are unknown. We conducted a modelled cost-effectiveness analysis of the SMARThealth intervention in rural villages of Malang district, Indonesia from the payer perspective over a 10-year period. A Markov model was designed and populated with epidemiological and cost data collected in a recent quasi-randomized trial, with nine health states representing a differing risk for experiencing a major CVD event. Disability-Adjusted Life Years (DALYs) were estimated for the intervention and usual care using disability weights from the literature for major CVD events. Annual treatment costs for CVD treatment and prevention were $US83 under current care and $US144 for those receiving the intervention. The intervention had an incremental cost-effectiveness ratio of $4288 per DALY averted and $3681 per major CVD event avoided relative to usual care. One-way and probabilistic sensitivity analyses demonstrated that the results were robust to plausible variations in model parameters and that the intervention is highly likely to be considered cost-effective by decision-makers across a range of potentially acceptable willingness to pay levels. Relative to current care, the intervention was a cost-effective means to improve the management of CVD in this rural Indonesian population. Further scale-up of the intervention offers the prospect of significant gains in population health and sustainable progress toward universal health coverage for the Indonesian population.