April 30, 2014

## Calculating the Cost-Effectiveness of Brilliance: A journey to understand DALYs and the assumptions we make (Part 2)

If you missed Part I: Intro to \$/DALY and Brilliance’s Cost-Effectiveness be sure to read that first!

Quick re-cap: DALY (disability-adjusted life year) is a metric used to help explain the impact of a disease or health condition in a particular place. Unlike some other metrics, it combines both mortality (death) and morbidity (disability) into a single number, so that non-fatal health conditions are appropriately accounted for as a cost to the health system. \$/DALY quantifies this mortality and morbidity measure in dollars to represent the cost-effectiveness of a health intervention.

In the previous post, we went step-by-step through the \$/DALY calculation to determine that Brilliance’s \$/DALY is \$29. In other words, it costs \$29 to avert the loss of one disability-adjusted life year in India due to untreated neonatal hyperbilirubinemia with Brilliance.

In this post we’ll be asking “So what?”

Part II: What does the \$/DALY metric tell us? How does Brilliance’s \$/DALY compare to other interventions?

1. What does the \$/DALY metric tell us?

a. How does jaundice compare to other diseases?

b. How does Brilliance compare to interventions for severe neonatal jaundice?

c. How does Brilliance compare across different locations?

2. Criticisms of \$/DALYs Analysis

3. Our conclusion (drum roll, please!)

What does the \$/DALY metric tell us?

The most common use for cost-effectiveness expressed as \$/DALY is to assist in prioritizing health interventions and informing policy decisions. Essentially, the goal of the \$/DALY metric is to improve global health by making it easier for stakeholders, including funders and policymakers, to compare different interventions.18 There are two main ways experts use \$/DALY to compare to interventions: (a) across diseases, and (b) across interventions for the same disease.

a. Compare across diseases

Let’s step back from Brilliance and D-Rev. Is severe jaundice a condition where we could be creating the most impact for our dollar—or our \$29?

We may also consider developing a solution to other public health problems, such as diarrheal illnesses. How cost-effective is it to invest in solving jaundice rather than other health issues? Generally, \$/DALY is an analysis used by large data-driven funding organizations to determine program priorities—does the organization get more years of life saved per dollar invested when they invest in diarrheal disease treatments or when they invest in severe jaundice treatments?

Brilliance’s cost-effectiveness ratio of \$29/DALY is comparable to the cost-effectiveness of sexually transmitted infection (STI) clinics to reduce HIV/AIDS in Andhra Pradesh.19 When comparing to several health interventions in Sub-Saharan Africa, treating hyperbilirubinemia with Brilliance, is more cost-effective than treating hepatitis B with a vaccine (approximately \$500/DALY), and treating diarrheal disease by providing a hand pump where clean water supply is limited (approximately \$100-300/DALY).20

The takeaway? Neonatal hyperbilirubinemia (severe jaundice) is a relatively inexpensive disease to tackle when compared to other diseases or health conditions. D-Rev could use this comparison to push policymakers and funders to focus on severe jaundice, by showing how much more cost-effective (in terms of maximizing impact) an investment in D-Rev or Brilliance is compared to investing in an organization focused on a competing health priority.

b. Compare across interventions for the same disease

\$/DALY cost-effectiveness is also a useful metric to compare different types of interventions that aim to solve the same problem. We could calculate the \$/DALY of competing products like GE or Natus’ phototherapy devices in India and make a comparison, or we could calculate the \$/DALY of another type of technology, such as a phototherapy device that uses CFL bulbs, to make a technological approach comparison. These comparisons would be useful for us, but unfortunately there is not enough price transparency in medical devices to make the cost estimates necessary to compare Brilliance to competing products.

c. Compare the same intervention across locations

As we continue to scale Brilliance to new locations outside of India and around the world, it will be useful to compare the \$/DALY of Brilliance across our target markets. Understanding the cost to the patient’s family in relation to the incidence rate of kernicterus in each region will help our team understand where Brilliance has the opportunity to create the biggest impact.

2. Criticisms of \$/DALYs

While this exercise is a powerful impact measure, determining \$/DALY is not an exact science and comes with limitations. Making decisions and setting priorities based on these types of calculations should be done with caution.

DALYs are essentially an economic measure of human productive capacity for the affected individual, and consequently do not capture other, non-economic aspects of diseases, such as emotional effects on friends and families.21 This is an especially critical oversight for families in our target markets caring for children with kernicterus, who require fulltime care.21

Non-economic effects are not taken into account in DALYs analysis, and even the economic burden has a purposefully limited scope. Based on D-Rev fieldwork, we know that the peripheral costs of jaundice treatment, such as the cost of travel to and from a hospital, can often be substantial and are critical to designing an intervention in context. However, the assessment of total cost in this analysis does not take into account indirect costs (beyond lost wages). Including these peripheral costs in the calculations also raises a question of interpretation. If an intervention appears low in cost-effectiveness because it requires much travel or waiting time, the fault may lie not with the intervention itself but with health facilities that are located far from the beneficiary population, are understaffed, and/or are inefficiently managed. For this reason, cost-effectiveness is estimated assuming a functional health system that does not impose prohibitive time costs on users.23

Lastly, while the rationale and source for each assumption along the calculation chain is explicitly cited there is still a compound effect of building multiple assumptions into a single calculation. Data, we all know aren’t perfect and even seemingly straight forward numbers have assumptions built in. Until 2014, for example, most of the data used to look at the global burden of kernicertus was based on data from wealthier countries, which is not a suitable proxy for many low-income countries. (Also, see our colleague Barrett Sheridan’s post “Ground Truthiness” on understanding Brilliance’s impact on the ground.) In the future, it will be useful for us to run sensitivity analyses on the calculations to determine how each assumption we make effects the final \$/DALY.

3. Our Conclusions

At D-Rev we continually evaluate, and quantify where possible, the impact of our products.

For each of our products, purchase price is one of the most important design constraints during product development, manufacturing, and scale but this \$/DALYs analysis goes one step further. \$/DALY with its particular focus on a health intervention as a whole—combining the purchase price with lost wages during treatment and the unique incidence rate in a target market—gives us a more well-rounded picture of a product’s cost-effectiveness than just the purchase price alone.

Beyond an internal evaluation of how Brilliance fits within the healthcare system, \$/DALY and other forms of cost-effectiveness analysis are essentially comparison tools. The power of this metric is in giving some cross-cutting guidance to assist in making decisions about what health intervention to invest in. At D-Rev, we want to know, not only how many deaths and disabilities Brilliance has averted, but whether designing and delivering Brilliance is the most efficient and powerful way for our small (and mighty!) organization to improve the health of poor populations around the world.

The driving force of conducting cost-effectiveness analysis “…is the notion that health resources should be allocated across interventions and population groups to generate the highest possible overall level of population health.”24 We hope that this analysis provides information to the public, to our funders, and to our partners about why we do what we do and reinforces our goal to minimize the burdens of disease and maximize health outcomes efficiently and sustainably.

Works Cited

• Access Economics PTY Limited for Cerebral Palsy Australia, “The Economic Impact of Cerebral Palsy inAustralia in 2007,” Access Economics Pty Limited, April 2008.

• Bhutani, Vinod K, and Lois H. Johnson. “Newborn Jaundice and Kernicterus—Health and Societal Perspectives.” Indian Journal of Pediatrics. 70. (2003): 407-16. Print.

• Center for Disease Control, “Kernicterus in Full-Term Infants—United States, 1994-1998,” Morbidity and Mortality Weekly Report (2001), accessed October 24, 2013, https://www.cdc.gov/mmwr/preview/mmwrhtml/mm5023a4.htm.

• Cline, B.K., R. Vilms, K. McGraw, H.H. Lou, K.M. Donaldson, and V.K. Bhutani. “Global Burden and Unmet Need for Hyperbilirubinemia Treatment.” 2009. Accessed March 24, 2014. https://d-rev.org/wp-content/uploads/2013/12/2011_PAS_Global_Unmet_Need_for_Phototherapy.jpg.

• Dandona, Lalit, SG Prem Kumar, G Anil Kumar, and Rakhi Dandona. “Cost-effectiveness of HIV prevention interventions in Andhra Pradesh state of India.” BMC Health Services Research 10 (May 10, 2010).

• Edejer, T. Tan-Torres, et al. “Making Choices in Health: WHO Guide to Cost-Effectiveness Analysis.”World Health Organization: n. pag. World Health Organization. Web. 26 Feb. 2014. https://www.who.int/choice/publications/p_2003_generalised_cea.pdf.

• Gold MR, Siegel JE, Russell LB, et al., editors. Cost-effectiveness in health and medicine. New York: Oxford University Press; 1996.

• “Human Development Reports: India.” UN Human Development Report. Last modified 2013. Accessed March 24, 2014. https://hdr.undp.org/en/countries/profiles/IND.

• “India.” The World Bank. Last modified 2011. Accessed March 24, 2014. https://data.worldbank.org/ country/india.

• Ip, Stanley, MD, and Et. al. “An Evidence-Based Review of Important Issues Concerning Neonatal Hyperbilirubinemia.” Pediatrics 114, no. 1 (July 1, 2004): 130-53.

• Laxminarayan, Ramanan, Jeffrey Chow, and Sonbol A. Shahid-Salles. Disease Control Priorities in Developing Countries. Washington DC, USA: World Bank, 2006.

• Musgrove P, Fox-Rushby J. Cost-Effectiveness Analysis for Priority Setting. In: Jamison DT, Breman JG, Measham AR, et al., editors. Disease Control Priorities in Developing Countries. 2nd edition. Washington (DC): World Bank; 2006. Chapter 15. Available from: https://www.ncbi.nlm.nih.gov/books/NBK11780/

• Thacker SB, Stroup DF, Carande-Kulis V, Marks JS, Roy K, Gerberding JL (2006). “Measuring the public’s health”. Public Health Rep 121 (1): 14–22.

• “UNICEF India Statistics,” https://www.unicef.org/infobycountry/india_statistics.html

• World Health Organization “Death and DALY estimates for 2004 by cause for WHO Member States: Persons, all ages” (xls). World Health Organization. 2002. Retrieved 2009-11-12, https://www.who.int/entity/healthinfo/global_burden_disease/gbddeathdalycountryestimates 2004.xls

• World Health Organization 2004. The global burden of disease: 2004 update. Geneva: WHO.

18 Laxminarayan, Chow, and Shahid-Salles, Disease Control Priorities in Developing, 35.
19 Dandona et al., “Cost-effectiveness of HIV prevention,” 5.
20 Laxminarayan, Chow, and Shahid-Salles, Disease Control Priorities in Developing, 35.
21 Thacker SB, Stroup DF, Carande-Kulis V, Marks JS, Roy K, Gerberding JL (2006). “Measuring the public’s health“. Public Health Rep 121 (1): 14–22.
22 Center for Disease Control, “Kernicterus in Full-Term Infants—United States, 1994-1998,” Morbidity and Mortality Weekly Report (2001), accessed October 24, 2013
23 Musgrove P, Fox-Rushby J. Cost-Effectiveness Analysis for Priority Setting. In: Jamison DT, Breman JG, Measham AR, et al., editors. Disease Control Priorities in Developing Countries. 2nd edition. Washington (DC): World Bank; 2006. Chapter 15.
24 T. Tan-Torres Edejer, et al. “Making Choices in Health: WHO Guide to Cost-Effectiveness Analysis.” World Health Organization: n. pag. World Health Organization. Web. 26 Feb. 2014. 3.