Resource Maximization in Global Health

A central issue in global health is how to maximize available resources. In other words, how can global health initiatives get the most bang for their buck? While human health has improved dramatically during the last century, grave inequities in health persist. To make further progress in health, meet new challenges, and reduce inequities, resources must be deployed effectively. In a time of unprecedented funding available for global health programs, it is more important than ever to assess which interventions actually work, how much they cost, and how they can best be implemented.(1)

Resource maximization is important because there is a limit on available resources. This is one of the basic axioms of economics: every direction of allocation competes for ‘scarce' resources. There are several limitations of concern to global health endeavors. First, there is a hard limit on resources, including funding, personnel, equipment, etc. A second limitation has to do with choices. Not all societal problems arise from poor health, and policy-makers must make certain choices concerning how to promote well-being. With various issues of concern to society—such as security, defense, and education—global health initiatives compete for attention and for resources. Scarce resources put a limit on what can be allocated to health. The attention limit of policy-makers puts an equally real limitation on what will be allocated toward health.

Evidence-Based Programs

The first important aspect of resource maximization is to spend funds wisely on programs that work. Best practices in health promotion are “those sets of processes and activities that are consistent with health promotion values/goals/ethics, theories/beliefs, evidence, and that are most likely to achieve health promotion goals in a given situation.”(2) For example, Unite For Sight applies best practices in public health and community eye care. Such practices involve providing quality patient care, eliminating social and economic barriers to care, partnering with local ophthalmologists, ensuring sustainability, and empowering communities.

Without an understanding of best practices, global health programs may fall into the pitfall of spending resources on the quantity of an intervention over its quality and potential impact. This can occur, for example, if an organization with limited funds decides that it can get the most out of its money by purchasing thousands of condoms and distributing them throughout a rural community in order to curb the rates of HIV transmission. Because condoms are inexpensive, the organization reasons that by purchasing more condoms, more people will be helped. However, evidence has shown that without proper instruction and reproductive health education, such an intervention is not likely to have much impact.(3) Thus, the organization essentially wasted resources by directing them toward an intervention that was not based in evidence. To avoid this pitfall, global health initiatives and organizations must strive to maximize their resources by researching best practices and by measuring the outcome of their work.

While the direction of funds toward evidence-based interventions avoids wasting resources, there remains another question in resource maximization. Given a multitude of evidence-based interventions and the reality of limited resources, how should the global health community choose between these interventions? Should resources be funneled to address the most burdensome diseases, toward prevention efforts, or toward programs that will help the most people, even if in a small way?

Cost-effectiveness Analysis

Cost-effectiveness analysis proposes one solution to this issue. Cost-effectiveness analysis is a method for assessing the gains in health relative to the costs of different health interventions.(4) It combines information about effective interventions (evidence-based interventions) with information about their costs. “It is not the only criterion for deciding how to allocate resources, but it is an important one because it directly relates the financial and scientific implications of different interventions.”(5) The basic calculation involves dividing the cost of an intervention by the expected health gain. Thus, as its name implies, cost-effective analysis takes into account both the cost of the intervention and how effective the intervention is likely to be.

Cost-effectiveness analysis helps identify neglected opportunities by highlighting interventions that are relatively inexpensive, yet have the potential to reduce the disease burden substantially. For example, each year more than a million young children die from dehydration when they become ill with diarrhea. Oral rehydration therapy dramatically reduces its severity and the associated mortality rate. The scientific evidence that this therapy can save lives was an important step in identifying this as a neglected opportunity for improving health. Moreover, demonstrating that it could cost only $2 to $4 per life year saved caused many countries to respond by promoting oral rehydration therapy, saving millions of lives.(6)

Measuring the Burden of Disease

Another tool designed to guide resource allocation is the disability adjusted life year (DALY). The DALY is a “health gap measure that extends the concept of potential years of life lost due to premature death to include equivalent years of 'healthy' life lost in states of less than full health, broadly termed disability.”(7) It measures the global burden of disease by providing a comprehensive and comparable assessment of mortality and loss of health due to diseases, injuries, and risk factors for all regions of the world.

The intended use of this indicator is fourfold: (1) to aid in setting health service priorities (both curative and preventive), (2) to aid in setting health research priorities, (3) to aid in identifying disadvantaged groups and targeting of health interventions, and (4) to provide a comparable measure of output for intervention, program, and sector evaluation and planning.(8)

This framework has been used by some to advocate DALYs as the best measurement of the health component of social welfare. In this line of reasoning, cost per DALYs is an “objective” way to maximize resources.(9) The basis of this argument is that resources should go toward diseases that are the most burdensome on the global population. When combined with cost-effectiveness analysis, this tool has become a popular way to determine the distribution of funds.

Pitfalls of DALYs and Cost-effectiveness Ideology

There have been critics of both DALYs and the cost-effectiveness ideology. Anand et al. argue that the conceptual and technical basis for DALYs is flawed and its assumptions and value judgments are open to serious question.(10) They argue that DALYs attempt to measure the burden of disease in a narrow sense:

“They [DALYs] represent the quantity of ill-health experienced by individuals through functional limitation and premature death. The burden that is measured does not reflect individuals' differential ability to cope with their functional limitation. Moreover, burdens which fall on family, friends, and society at large (e.g. the economic cost of illness) are not included.”

In addition, the story of multi-drug resistant tuberculosis presents a criticism to the cost-effectiveness ideology that the World Bank and the World Health Organization employed in the late 1990s.(11) Based on a cost-effectiveness model, many organizations chose not to treat multi-drug resistant tuberculosis in impoverished settings. They cited the high price of MDR-TB drugs (a reason also used to justify not treating HIV/AIDS in the Global South), as well as the fact that MDR-TB only affects a small proportion of the population to justify the non-allocation of resources.

Many researchers and global health activists had objective goals: they wanted to treat TB in the cheapest way possible, which is theoretically good as it would maximize health benefits in the end. Yet the way in which the cost-effective method was employed was neither objective nor valid. The underlying assumptions of cost-effectiveness went on to shape supposedly “objective” quantitative measurements which resulted in the denial of available healthcare to those most in need. A key assumption underlying the goal of cost-effectiveness—the assumption of limited resources—was just that: a position and a concept, and, as was eventually realized, adjustable in the face of moral obligations. While DALYs and cost-effectiveness analysis are valuable tools in the effort to maximize health benefits given limited resources, it is crucial to remember that approaching problems with the cost-effectiveness model inevitably narrows the solutions that are proposed.

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(1) Jamison DT, Breman JG, Measham AR, et al., editors. Priorities in Health. Washington (DC): The International Bank for Reconstruction and Development / The World Bank; 2006. Chapter 3, Cost-Effectiveness Analysis. Available from: Accessed 10 December 2019.

(2) Kahan, Barbara, and Michael Goodstadt. “The IDM Manual: a Guide to the IDM (Interactive Domain Model) Best Practices Approach to Better Health.”Centre for Health Promotion, University of Toronto, May 2005, Accessed 10 December 2019.

(3) Hendriksen, E. S., Pettifor, A., Lee, S. J., Coates, T. J., & Rees, H. V. (2007). Predictors of condom use among young adults in South Africa: The reproductive health and HIV research unit national youth survey. American Journal of Public Health97(7), 1241-1248.

(4) Jamison DT, Breman JG, Measham AR, et al., editors. Priorities in Health. Washington (DC): The International Bank for Reconstruction and Development / The World Bank; 2006. Chapter 3, Cost-Effectiveness Analysis. Available from: Accessed 10 December 2019.

(5) Ibid.

(6) Ibid.

(7) Havelaar, A. WHO Estimates of the Global Burden of Foodborne Diseases, 2010. 14 Oct. 2015, Accessed 10 December 2019.

(8) Murray, C J. “Quantifying the Burden of Disease: the Technical Basis for Disability-Adjusted Life Years.”Bulletin of the World Health Organization, World Health Organization, 1994, Accessed 10 December 2019.

(9) Garber, et al. “Economic Foundations of Cost-Effective Analysis.”National Bureau of Economic Foundations, 1 Sept. 1992, Accessed 10 December 2019.

(10) Anand, S., & Hanson, K. (1997). Disability-adjusted life years: a critical review. Journal of health economics16(6).

(11) Kim, J. Y., Shakow, A., Mate, K., Vanderwarker, C., Gupta, R., & Farmer, P. (2005). Limited good and limited vision: multidrug-resistant tuberculosis and global health policy. Social Science & Medicine61(4), 847-859.