Are user fees a barrier to health care in poor countries?

The 1987 Bamako declaration promoted user or consultation fees for health care as a means to raise revenue and improve the quality of services. However, user fees may pose a barrier to access, and hence the key Sustainable Development Goal of Universal Health Coverage (UHC), for the global poor who typically have a high elasticity of demand for health services. The evidence has been mixed though on the impact of adding or removing user fees. A Cochrane review found that utilisation of services typically declined significantly with the introduction of fees and that quality was often found to improve with fees, but they also questioned the reliability of these studies due to a “high risk of bias”. Indeed, the evidence can be conflicting as to the effect of user fees on health service utilisation. Consider the following two studies from two similar countries: Malawi and Zambia.

The first looks at the effect the introduction and removal user fees had on health centre outpatient attendances, new diagnoses of malaria, and HIV diagnoses in a rural district of Malawi (which I should declare I authored!) Of 13 centres in Neno district, four were operated by the Christian Health Association of Malawi, of which one has always charged user fees and three introduced them in July 2013. The other centres were operated by the Ministry for Health and an NGO, Partners In Health, and did not charge fees. In July 2015, one centre removed user fees. These changes in charging status created a neat natural experiment. A plot of outpatient attendances shows what happened:

Figure 3

Even without modelling it is clear what happened – attendances dropped with the introduction of user fees and increased when they were removed. Similar changes were seen in new malaria and HIV diagnoses Further analysis also suggested patients weren’t moving between centres to avoid fees.

The second study, published this week, looks at a 2006 policy to remove user fees for publicly-funded health care facilities in rural districts across Zambia. The policy was instigated by the Zambian president as a step towards UHC, but was implemented haphazardly with funding not being completely in place and districts choosing to distribute the funding they received in different ways. Using data from a repeated cross-sectional health survey, the corresponding plot of the effects of the policy is:


Evident from this and reinforced by their synthetic control analysis, the policy did little to change the proportion of people seeking health care. The key impact of the policy was to reduce out of pocket expenditure as it seems people switched from using private providers to public providers. So why do the results of these studies, with seemingly similar ‘treatments’ in similar poor rural populations, differ so much?

In an earlier study of the Zambian policy it was found that outpatient attendances recorded in routine data – the same data used in the Malawi study above – there were large increases in use of public facilities when user fees were removed. The new study adds evidence though that this increase was a result of people switching from private to public providers. In Neno district, Malawi there are no private providers – only those in the study. Nevertheless, private providers also charge, so health care use in the face of fees was markedly higher in Zambia than Neno, Malawi. Perhaps there are relevant differences then in the populations under study.

Zambia, even in 2006, was much wealthier than Malawi in 2013. GDP per capita in comparable dollars was $1,030 in 2006 Zambia and $333 in 2013 Malawi. And Neno district is among the poorest in Malawi. The Malawi study population may be significantly poorer then than that in Zambia, and so have yet more elastic demand. Then again, Zambia is one of the most unequal countries in the world, its wealth generated from a boom in the copper price and other commodities. Its Gini coefficient is 57.5 as compared to Malawi’s 43.9. Thus, one may expect rural Zambians to perhaps be comparable to those in Malawi despite GDP differences. Unfortunately, there aren’t further statistics in the paper to compare the samples – and indeed no information on the relative prices of the user fees. And further, the Zambia paper does look at the poorest 50% of people separately and finds little difference in the treatment effect although there does appear to be large levels of heterogeneity in the estimated treatment effects between districts.

Differences in conclusions may also results from differences in data. For example, the Zambia study looked at changes in the reported use of formal health care among people who had an illness recently, whereas the Malawian study looked at outpatient attendances and diagnoses. Perhaps a difference could arise here such as reporting biases in the survey data.

It is not clear why results in the Zambian study differ from those in the Malawian one and indeed many others. It certainly shows the difficulty we have understanding the effect even small charges can have on access to care even as the quality of the evidence improves.


Sam Watson’s journal round-up for 10th October 2016

Every Monday our authors provide a round-up of some of the most recently published peer reviewed articles from the field. We don’t cover everything, or even what’s most important – just a few papers that have interested the author. Visit our Resources page for links to more journals or follow the HealthEconBot. If you’d like to write one of our weekly journal round-ups, get in touch.

This week’s journal round up-is a special edition featuring a series of papers on health econometrics published in this month’s issue of the Journal of the Royal Statistical Society: Series A.

Healthcare facility choice and user fee abolition: regression discontinuity in a multinomial choice setting. JRSS: A [RePEcPublished October 2016

Charges for access to healthcare – user fees – present a potential barrier to patients in accessing medical services. User fees were touted in the 1980s as a way to provide revenue for healthcare services in low and middle income countries, improve quality, and reduce overuse of limited services. However, a growing evidence base suggests that user fees do not achieve these ends and reduce uptake of preventative and curative services. This article seeks to provide new evidence on the topic using a regression discontinuity (RD) design while also exploring the use of RD with multinomial outcomes. Based on South African data, the discontinuity of interest is that children under the age of six are eligible for free public healthcare whereas older children must pay a fee; user fees for the under sixes were abolished following the end of apartheid in 1994. The results provide evidence that removal of user fees resulted in more patients using public healthcare facilities than costly private care or care at home. The authors describe how their non-parametric model performs better, in terms of out-of-sample predictive performance, than the parametric model. And when the non-parametric model is applied to examine treatment effects across income quantiles we find that the treatment effect is among poorer families and that it is principally due to them switching between home care and public healthcare. This analysis supports an already substantial literature on user fees, but a literature that has previously been criticised for a lack of methodological rigour, so this paper makes a welcome addition.

Do market incentives for hospitals affect health and service utilization?: evidence from prospective pay system–diagnosis-related groups tariffs in Italian regions. JRSS: A [RePEcPublished October 2016

The effect of pro-market reforms in the healthcare sector on hospital quality is a contentious and oft-discussed topic, not least due to the difficulties with measuring quality. We critically discussed a recent, prominent paper that analysed competitive reforms in the English NHS, for example. This article examines the effect of increased competition in Italy on health service utlisation: in the mid 1990s the Italian national health service moved from a system of national tariffs to region-specific tariffs in order for regions to better incentivise local health objectives and reflect production costs. For example, the tariffs for a vaginal delivery ranged from €697 to €1,750 in 2003. This variation between regions and over time provides a source of variation to analyse the effects of these reforms. The treatment is defined as a binary variable at each time point for whether the regions had switched from national to local tariffs, although one might suggest that this disposes of some interesting variation in how the policy was enacted. The headline finding is that the reforms had little or no effect on health, but did reduce utilisation of healthcare services. The authors interpret this as suggesting they reduce over-utilisation and hence improve efficiency. However, I am still pondering how this might work: presumably the marginal benefit of treating patients who do not require particular services is reduced, although the marginal cost of treating those patients who do not need it is likely also to be lower as they are healthier. The between-region differences in tariffs may well shed some light on this.

Short- and long-run estimates of the local effects of retirement on health. JRSS: A [RePEcPublished October 2016

The proportion of the population that is retired is growing. Governments have responded by increasing the retirement age to ensure the financial sustainability of pension schemes. But, retirement may have other consequences, not least on health. If retirement worsens one’s health then delaying the retirement age may improve population health, and if retirement is good for you, the opposite may occur. Retirement grants people a new lease of free time, which they may fill with health promoting activities, or the loss of activity and social relations may adversely impact on ones health and quality of life. In addition, people who are less healthy may be more likely to retire. Taken all together, estimating the effects of retirement on health presents an interesting statistical challenge with important implications for policy. This article uses the causal inference method du jour, regression discontinuity design, and the data are from that workhorse of British economic studies, the British Household Panel Survey. The discontinuity is obviously the retirement age; to deal with the potential reverse causality, eligibility for the state pension is used as an instrument. Overall the results suggest that the short term impact on health is minimal, although it does increase the risk of a person becoming sedentary, which in the long run may precipitate health problems.


Other articles on health econometrics in this special issue:

The association between asymmetric information, hospital competition and quality of healthcare: evidence from Italy.

This paper finds evidence that increased between hospital competition does not lead to improved outcomes as patients were choosing hospitals on the basis of information from their social networks. We featured this paper in a previous round-up.

A quasi-Monte-Carlo comparison of parametric and semiparametric regression methods for heavy-tailed and non-normal data: an application to healthcare costs.

This article considers the problem of modelling non-normally distributed healthcare costs data. Linear models with square root transformations and generalised linear models with square root link functions are found to perform the best.

Phantoms never die: living with unreliable population data.

Not strictly health econometrics, more demographics, this article explores how to make inferences about population mortality rates and trends when there are unreliable population data due to fluctuations in birth patterns. For researchers using macro health outcomes data, such corrections may prove useful.