Financial Risk Protection

A couple of months ago in this blog, we looked at financial aspects of delivering surgical care. Today we view this from another perspective: that of the patient facing the financial consequences of requiring surgical intervention, or Financial Risk Protection.

It is not only the cost of providing health care that interferes with its availability but also, the costs to the individual of obtaining that care comprise a major barrier for many. Further, in addition to the costs of the care itself, a significant portion of these costs are not medically related, but rather are costs of transportation and other logistics.

In order to determine how access to surgical care might be adversely affected by prohibitive costs, Shrime, Dare, Alkire, O’Neill, and Meara constructed a stochastic model, reported in Catastrophic expenditure to pay for surgery worldwide: a modelling study, Lancet Glob Health (2015);3(S2):S38-45. Using readily available World Bank data, they modeled the number of people in a country that would require surgical care over a one year period, then modeled the costs, medical and non-medical, that would be incurred. This included the out of pocket component of those costs, and the proportion of household income that would constitute those costs. The findings, while perhaps not surprising, were sobering. Across the globe, when taking into account only medical costs, 33 million people were ensnared by catastrophic expenditure due to requiring surgical care, and 50% of the entire global population was found to be at risk for such. With non-medical costs included, this 33 million morphs to 81 million.

Overwhelmingly, this burden was found to fall on the poor (no surprise there). In low-income countries, even the richest wealth quintile was at risk, almost equally with the poorest. In LMICs, the richest quintile was still affected, though at about half the rate of the other four quintiles. In HICs, though, the risk to the poorest quintile was less than that of the wealthiest in LICs and LMICs. The medical component only of these costs was a bit kinder to the upper wealth quintiles of LICs, LMICs, and upper middle income countries, but it also must be considered that to the individual facing catastrophic costs, the source of those costs is not particularly relevant. It also is true that among the poor, the medical component alone reaches the threshold of catastrophic expenditure; non-medical costs may push them further into abject poverty but do not change the binary condition of financial catastrophe. With some degree of wealth, the effect of non-medical costs becomes of greater import.

It is pointed out that people in LMICs are more at risk than those in LICs because the costs of surgery are higher in LMICs. This fact, that costs of accessing surgical care may increase out of proportion to individual income as economic status of a country improves, is an important finding. The ramifications are for health care financing policy as countries advance on the economic scale. It also is important to note that these estimates do not take into consideration the people who forego care because of its costs, or the expenditure incurred because of this lack of care. Loss of wages and decreased productivity for the patient as well as for family members providing care for the patient also fall out of the realm of this model. Similarly, the threshold for what constitutes catastrophic expenditure (10% of household income was used in this study) likely markedly underestimates the incidence among the poor. When a large proportion of income is needed for food, or for those people bordering on poverty, essentially any expenditure is catastrophic regardless of definitions.

The map reproduced below indicates the risk of catastrophic expenditure for people in all countries if surgical care becomes necessary.

The expansion of access to surgical care inherently brings with it the financial risks of utilization of that care. The WHO makes the point that improving health is only one of three key goals for health systems; providing financial protection and equitable distribution of health and financial protection among the population are of equal importance. The varied effects of policies that address access to care and the financial ramifications of such access were modeled exquisitely in Disease Control Priorities 3: Essential Surgery, Chapter 19, Task-sharing or public finance for expanding surgical access in rural Ethiopia: an extended cost-effectiveness analysis, by Shrime, Verguet, Johansson, Desalegn, Jamison, and Kruk. The model specifically was constructed from Ethiopian data, but its findings are broadly applicable.

This model considered the direct costs of surgical care but also the non-medical costs of travel, food, and lodging, and looked at the effect on health and financial catastrophe of various coverages for these services. The authors also included the concept of task sharing as another key variable that can affect both health and cost. They did not include lost productivity, wages, utility, or effect on family in their cost analysis.

Condensing this study considerably, it was found that covering the surgical costs alone (Universal Public Financing, or UPF) brought health benefits mostly to the poorest quintiles. Richer people already had access, so their health changed little. The rich did, however, benefit from UPF in a decrease in financial risk. Concurrently, the poor saw an increase in financial risk, and would have seen an increase in impoverishment had the baseline level of poverty not already been so great. Task sharing also aided health but increased poverty, mostly among the poorer quintiles, as access was increased.

When non-medical costs were covered, health benefits increased across the board because of increased demand, but increased much more to the poorest. Financial risk protection increased considerably, but again, the benefits went more to the rich: the rich have more financial risk to begin with, so have more benefit when that risk is diminished. The variability among wealth quintiles is far more nuanced than this review discusses; the reader is referred to Table 3 of this chapter for more in-depth information in this regard.

The two key points from this chapter are (1) efforts to provide increased access to surgical care include significant trade-offs in the distribution of benefits, and who reaps these benefits depends on what the policy entails, and (2) poorer health and impoverishment are only prevented when people do not face the non-medical costs of care as well as the medical.

Rickard et al, Risk of Catastrophic Health Expenditure in Rwandan Surgical Patients with Peritonitis, World J Surg (2017) https://doi.org/10.1007/s00268-017-4368-x, examined the financial effects of a major surgical episode on patients in a LIC with a very functional community-based health insurance scheme in place. Two findings stand out. First, the medical expenses (90% of which were paid by insurance in covered patients) represented only a portion of total costs for these patients, such that 28% were still at risk of catastrophic expenditure. Second, in this LIC with a GDP per capita of 700 USD per year, a health insurance scheme covering 74% of the population and reducing the risk of catastrophic expenditure from a surgical need to 28% is possible.

Of further interest is the breakdown of these in-hospital medical expenses. While the methods and intent were not of the depth of the Abbott paper discussed below, these figures are relevant and are reproduced below, adapted from table 2 in the paper. Presumably Procedures includes physician charges, facility overhead, and staff salaries.

Although it is a study conducted in a high income country, Trading Bankruptcy for Health: A Discrete Choice Experiment (2017)http://dx.doi.org/10.1016/j.jval.2017.07.006 by Shrime, Weinstein, Hammitt, Cohen, and Salomon investigates the issue of how people value health in relation to financial solvency. Analogous to studies determining the value of a statistical life, this study examined the trade-off between the probabilities of cure and those of remaining solvent. The overarching conclusion from this study is that people have widely differing preferences, and that demographics are not a good predictive factor for determining these preferences. Almost one-third of the US population stated a preference for “cure at all costs,” i.e., health at the expense of financial solvency, one-fifth valued health and solvency essentially equally, and one-twelfth valued solvency at the complete expense of health. The majority of people were indeed willing to trade some degree of health for financial protection. While extrapolating these results to LMICs is fraught with difficulty, this study may well reveal some aspects of human nature: cure is valuable, but so is financial security. The paper makes the very plausible statement that “Arguably, financial ruin is an equally far-reaching iatrogenic ‘complication’ [of health care].”

The overwhelming conclusion of studies of financial risk protection is that it is a component of the disease process that must be addressed in health care policy just as delivery of care is addressed. While HICs may often have more availability of health care services and technology, without financial risk protection the populace still lacks appropriate access to care.