Enhancing Global Health through Cost-Effectiveness Analysis

By Thanusha Pillay

June 28, 2024

Introduction: The Value of Cost-Effectiveness Analysis in Global Health

Cost-effectiveness analysis (CEA) in global health is crucial for optimising resource allocation and improving health outcomes. This study explores the methodologies and findings from recent research on CEA, focusing on interventions for HIV/AIDS, malaria, syphilis, and tuberculosis. This research allows governments to prioritise resources within the context of their own economy and epidemiology.

Understanding Cost-Effectiveness Analysis

Cost-effectiveness analysis evaluates the economic efficiency of healthcare interventions by comparing their costs and health outcomes. The primary metric used is the incremental cost-effectiveness ratio (ICER), which measures the cost per quality-adjusted life-year (QALY) or disability-adjusted life-year (DALY) gained. A lower ICER indicates a more cost-effective intervention. Country-specific evidence for all recommended interventions for HIV/AIDS, tuberculosis, malaria, and syphilis is lacking. Meta-regression methods can transfer cost-effectiveness estimates between countries by analysing the association between ICERs and country-specific factors.

Methodology and Data Sources

The study utilised data from two registries maintained by Tufts University: the Cost-Effectiveness Analysis (CEA) Registry and the Global Health CEA Registry. These registries include peer-reviewed articles with health outcomes measured in QALYs or DALYs. The analysis focused on interventions for HIV/AIDS, malaria, syphilis, and tuberculosis, covering 128 countries eligible for Global Fund support.

https://www.thelancet.com/cms/attachment/a3f2d97c-f03a-49f1-9637-b38e4ece987e/gr2.jpg

Figure 1. Flow diagram for meta-regression analysis based on data from cost-effectiveness analyses registries

Key Findings

  1. HIV/AIDS Interventions

    The study analysed 258 ICERs from 57 articles on antiretroviral therapy (ART) for HIV/AIDS. The results showed that ART is highly cost-effective, particularly in low-income regions. The burden variable was negatively associated with ICER, indicating that higher disease burden leads to more cost-effective interventions.

  2. Malaria Prevention

    For malaria prevention, 74 ICERs from ten articles were analysed. The interventions included bed nets and intermittent preventive treatment for pregnant women and infants. The findings highlighted the cost-effectiveness of these interventions, especially in regions with high malaria prevalence.

  3. Syphilis Diagnostics

    The study included 111 ICERs from four articles on syphilis diagnostics. The results demonstrated that syphilis diagnostics are cost-effective in most regions, with test sensitivity being a crucial factor. No ratios were published for high-income countries, likely due to the widespread adoption of these diagnostics.

  4. Tuberculosis Interventions

    The analysis covered 89 ICERs from 13 articles on tuberculosis diagnostics and treatment. The findings indicated that tuberculosis diagnostics and treatment are cost-effective, particularly in regions with high disease burden. The cost variable was significant in predicting ICERs for these interventions.

 

Figure thumbnail gr3a

https://www.thelancet.com/cms/attachment/42284242-e0d0-4c6e-9db5-39d03b1c4abd/gr3b.jpg

Figure 2. League tables of interventions to avert the burden of HIV/AIDS, malaria, syphilis, and tuberculosis ranked by median incremental cost-effectiveness ratio in India (A), Indonesia (B), Nigeria (C), Peru (D), Sudan (E), and Ukraine (F), in 2019 US$

Box plots show median estimates and IQRs, with whiskers indicating 95% uncertainty intervals. This figure presents the league tables for the country in each GBD super-region (excluding the high-income super-region) that has the highest sum of DALYs from HIV/AIDS, malaria, and tuberculosis. Note that x-axis scales vary between plots. In panel F, no malaria-based interventions are presented because Ukraine is certified malaria-free. For IPT for pregnant women, 0–11 months, the infants aged 0–11 months are the beneficiaries of the intervention. Interventions without an age range are applicable for all age groups. All interventions are eligible for Global Fund support, unless otherwise indicated. The ICERs might be lower-bound estimates when a country is not eligible for support for that cause.

ART, antiretroviral therapy; DALY, disability-adjusted life-year; GBD, Global Burden of Diseases, Injuries, and Risk Factor Study; GDP, gross domestic product; ICER, incremental cost-effectiveness ratio; IPT, intermittent preventive treatment for malaria; MSM, men who have sex with men; Option B+ refers to HIV/AIDS screening for pregnant women and lifelong ART;  PREP, pre-exposure prophylaxis. *Interventions not eligible for Global Fund support.

Implications for Global Health

The findings from this study have significant implications for global health policy. By prioritising interventions with the lowest ICERs, countries can maximise the impact of their healthcare budgets. This approach eliminates the need for a single threshold for all healthcare funding decisions, allowing for more nuanced and effective resource allocation.

Challenges and Limitations

Despite the promising findings, the study faced several challenges. The paucity of published cost-effectiveness analyses for key interventions and the exclusion of dominated results limited the analysis. Additionally, the heterogeneity in published ICERs and the exclusion of some cost-saving results posed challenges.

Future Directions

Future research should focus on expanding the sample size by including more cost-effectiveness analyses. Converting ICERs from cost per HIV infection averted to cost per DALY averted could provide more comprehensive insights. Also, exploring covariates specific to cause-type groups and intervention coverage could improve the accuracy of predictions.

Conclusion

Cost-effectiveness analysis is a vital tool for optimising healthcare resource allocation. By understanding the economic efficiency of various interventions, policymakers can make informed decisions that maximise health outcomes. The findings from this study highlight the importance of prioritising interventions with the lowest ICERs to achieve the greatest impact.

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