In the translation of health technology innovations into actual public health, among the most consequential decisions to be made is what to charge the end user. Achieving sufficient coverage with essential tools to control diseases like HIV and malaria requires price subsidies, particularly in low-income countries. Subsidies are necessary because willingness to pay and ability to pay are both assumed to be low in these settings. Economic theory predicts that willingness to pay will be too low because individual demand for essential health tools will not take community benefits, or externalities, into account. Ability to pay is likely low because of poverty. Owing to their crucial role in attaining high levels of coverage, subsidies for preventive, diagnostic, and treatment technologies make up a substantial portion of donor funding for infectious disease control.1
While the need for subsidies is clear, the appropriate level of subsidy is not clear, and is often chosen based on guesses and trial and error. Higher subsidies should increase coverage, with the greatest coverage occurring when the subsidy is 100% (ie, the product is free). However, higher subsidies can pose trade-offs with respect to targeting products to the highest-value users.2 A concern about free distribution of health tools such as insecticide-treated nets to prevent malaria, water purification kits to prevent diarrheal disease, and HIV self-tests is that anyone will take these tools when they are free—including people who do not need them and will not use them. If people who value and need tools most are also the ones most willing to pay, then lower subsidy levels could be a cost-effective approach to allocating scarce resources. Arguments for cost sharing (ie, partial rather than full subsidies) are generally based on this reasoning. However, cost sharing can also screen out the poorest households, who have limited financial resources but need the product most. The optimal subsidy will depend on how sensitive people are to price and how successfully price functions as a targeting mechanism.
Chang and coauthors3 add strong evidence to the growing body of work suggesting that even small amounts of cost sharing for health products can have substantial effects on uptake in low-income countries.2,4 Chang et al3 used a randomized trial to evaluate the impact of various distribution strategies—including variation in pricing, distribution point, and messaging—on demand for rapid HIV self-tests in Zimbabwe. Households were given vouchers that could be redeemed for a test, with randomly assigned prices between $0 (full subsidy) and $3, and a cross-cutting random assignment of distribution point (public sector vs retail sector) and of promotional messaging. The authors found extremely high price sensitivity, with 32.5% of households redeeming their vouchers for the test at the full subsidy and only 0.8% willing to pay $3 for it. Furthermore, the most dramatic response to subsidy variation was in the comparison of the full subsidy ($0) with the nearly full subsidy ($0.50); in this case, demand decreased by more than 25 percentage points.
Several key takeaways emerge from this study. First, increasing subsidies for HIV self-tests, which currently cost $3 to $6 (subsidized) in the public sector, could dramatically increase uptake. Second, higher prices do not appear to improve targeting. On the contrary, the most extreme price sensitivity was observed in the highest-priority populations, with demand among people who had never been tested before being 23 percentage points lower at $0.50 than at $0. Unfortunately, the study does not report whether the tests were used, the actual test results, or any behavior change that resulted from the testing, such as condom use or initiation of antiretroviral therapy. It is also not known whether the tests obtained through the study simply substituted for tests people would have gotten elsewhere. A full cost-benefit assessment would require a more complete accounting of test results and behavior change. However, even if cost sharing had very beneficial effects on targeting—eg, if rates of HIV-positive test results were substantially higher for people paying $0.50 than for people getting a free test—free distribution would still most likely be superior to cost sharing in getting more tests to HIV-positive people because of the enormous dampening effect of cost sharing on uptake.
These results reinforce findings from previous randomized trials evaluating variation in subsidies for health products in low-income countries that have found uptake to be extremely price sensitive.2,4,5 For example, Cohen and Dupas5 found that an increase in the price of insecticide-treated nets from $0 to $0.60 reduced uptake by 60 percentage points. While price dramatically affected demand, price had no effect on targeting, with no difference in the probability of actually using the net if it was free, suggesting that free distribution was superior to cost sharing in this setting. Where the results of the study by Chang et al3 diverge from most past work is that uptake of HIV self-tests was far from universal even when tests were offered for free. There are many barriers to HIV testing that are not present for other products, eg, concerns about privacy and access to treatment. But uptake of free tests was also likely dampened because participants had to travel to redeem the voucher. Recent research has shown that so-called micro-ordeals—such as traveling, waiting in line, or filling out paperwork—can substantially influence demand for health products.6 Researchers are actively exploring whether micro-ordeals can actually be used beneficially in the distribution of health products, functioning as an alternative targeting mechanism to price, without having the negative effects that price can have on screening out the poorest households.
Why is price sensitivity so high for many essential, life-saving products? First, there are several unique aspects of zero financial price that likely substantially increase demand relative to cost sharing. Poor households who live off of subsistence agriculture do not hold much wealth in the form of cash, but rather in crops and minor assets. Even small amounts of cash are difficult to produce, particularly with many other competing priorities such as school fees and medications. Second, when a product is free, households do not need to discuss and agree on what they are willing to pay and how they will pay it. Third, for many health tools, while people are aware of their value and want to purchase them, it is too easy and tempting to put off their purchase until another day and instead use their limited cash for more immediate needs. Indeed, a randomized trial exploring the effect of subsidy variation for antimalarial medication in Kenya found that households were extremely insensitive to price.7 The contrast between price sensitivity for preventive products (like bed nets) and treatment products (like antimalarial drugs) speaks to the strong role of salience and immediate needs in the financial decisions of low-resource individuals.8
There are a number of other trade-offs introduced by subsidies that most of this literature does not take into account, such as the impact of free distribution on the sustainability of private markets for products and the role of cost sharing in helping to sustain weak and underfunded health services. Subsidy policy going forward should carefully weigh all of the evidence on behavioral responses to subsidies, recognizing that even small changes in price can have large effects on population coverage of essential health tools.
Published: August 28, 2019. doi:10.1001/jamanetworkopen.2019.9810
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Cohen JL. JAMA Network Open.
Corresponding Author: Jessica L. Cohen, PhD, Harvard T.H. Chan School of Public Health, 665 Huntington Ave, Boston, MA 02115 (email@example.com).
Conflict of Interest Disclosures: None reported.
Cohen JL. The Enduring Debate Over Cost Sharing for Essential Public Health Tools. JAMA Netw Open. 2019;2(8):e199810. doi:10.1001/jamanetworkopen.2019.9810
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