Cost-Effectiveness of Scaling Up Modern Family Planning Interventions in Low- and Middle-Income Countries: An Economic Modeling Analysis in Indonesia and Uganda
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The aim was to estimate the long-term cost-effectiveness of improved family planning interventions to reduce the unmet need in low- and middle-income countries, with Indonesia and Uganda as reference cases.
The analysis was performed using a Markov decision analytic model, where current situation and several scenarios to reduce the unmet need were incorporated as the comparative strategies. Country-specific evidence was synthesized from the demographic and health survey and published studies. The model simulated the sexual and reproductive health experience of women in the reproductive age range over a time horizon of women’s reproductive years, from the healthcare payer perspective. Modeled outcomes included clinical events, costs and incremental cost-effectiveness ratios (ICERs) expressed as cost per disability-adjusted life year (DALY) averted. Deterministic and probabilistic sensitivity analyses were conducted to assess the impact of parameter uncertainty on modeled outcomes.
In the hypothetical cohort of 100,000 women, scenarios to reduce the unmet need for family planning would result in savings within a range of US$230,600–US$895,100 and US$564,400–US$1,865,900 in Indonesia and Uganda, respectively. The interventions would avert an estimated 1859–3780 and 3705–12,230 DALYs in Indonesia and Uganda, respectively. The results of our analysis indicate that scaling up family planning dominates the current situation in all scenarios in both countries, with lower costs and fewer DALYs. These results were robust in sensitivity analyses.
Scaling up family planning interventions could improve women’s health outcomes substantially and be cost-effective or even cost saving across a range of scenarios compared to the current situation.
The model used in this study was provided to the journal’s peer reviewers for their reference when reviewing the manuscript.
NZ, FR and MJP designed the study. NZ, ADIvA, DS and MJP developed and analyzed the economic model. NZ and ADIvA validated the model and interpreted the results. DS and QC contributed to the development and analysis of the statistical approach. NZ prepared the first draft of the report. All authors edited and approved the final version.
Compliance with Ethical Standards
No sources of funding were used to conduct this study or to prepare this manuscript.
Conflict of Interest
NZ was a part-time researcher at i + Solutions. FR is employed by i + Solutions. MJP has received grants and honoraria from various pharmaceutical companies, including companies that might be interested in the content of this article. ADIvA, DS and QC report no conflicts of interest that are relevant to the content of this article.
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