Traditionally epidemiologists who worked on the relationship between wealth and disease were concerned with the effect of the first on the second. But, of course, disease can affect wealth, and economists like Jeffrey Sachs spotted the resulting circularity: poverty -> disease -> more poverty -> more disease. Increasingly, clinicians have started to worry about the catastrophic costs of disease and my colleague Bertie Squire from Liverpool School of Tropical Medicine is searching for treatment pathways to mitigate the financial consequences of recurrent tuberculosis. The Oregon experiment, reported in your News Blog, shows that the most obvious benefit from extending insurance coverage to the un-insured lies in reducing the incidence of catastrophic loss.
Catastrophic loss: “Events whose consequences are extremely harsh in their severity, relating to one or more losses such as bankruptcy, total loss of assets, or loss of life.” (The Law Dictionary, 2017).
An important question then, is how generous can publically financed insurance be? Or, to put the question another way, how can the affordability of health care be measured? This is a rather different question to that of the affordability of a particular new technology – a question of its Incremental Cost Effectiveness Ratios. This is because HTA is designed to determine the upper bound on ‘affordability’, while the fiscal question of affordability as a whole is concerned with total expenditure.
A paper in a recent issue of JAMA proposes an approach based on the total health costs divided by the median household income. This might be a useful rule of thumb, but it is beset by problems, as pointed out in two leading articles.  One such problem arises from the observation that some of the costs of health care / insurance premiums likely come out of household incomes – companies would probably pay employees more if it were not for the insurance premiums – so there is some double counting going on. More fundamentally, affordability cannot be inferred simply by the proportion of expenditure going on health care. One could argue, for instance, that the richer the country (higher the per capita GDP), the greater should be the expenditure on health. One way to get at the affordability construct would be to examine the cost of health care as a proportion of money left over after subtracting the ‘essentials’ of housing, food, clothing and transport to and from school / work. Another would be to calculate the effect of health care costs on how many families tip over into bankruptcy or teeter on the edge thereof. Unaffordability would still vary by type of family and type of insurance system, especially in a variegated health system like that in the USA. A simple number, like proportion of GDP spent on health, can only give a very coarse-grained idea of the consequences of increasing or decreasing the proportion of resources dedicated to health care. It is also important to consider the effect of high health care costs on the broader economy. There is always a danger that, absent price signals, the allocation to health will exceed what can be justified in terms of the benefit realised. That is to say that, given information asymmetries, health care will be driven more by provider than consumer needs.
— Richard Lilford, CLAHRC WM Director
- Baicker K, Taubman SL, Allen HL, et al. The Oregon Experiment – Effects of Medicaid on Clinical Outcomes. N Engl J Med. 2013; 368: 1713-22.
- Emanuel EJ, Glickman A, Johnson D. Measuring the burden of health care costs on US families: the Affordability Index. JAMA. 2017; 318(19): 1863-4.
- Antos J, Capretta JC. Challenges in Measuring the Affordability of US Health Care. JAMA. 2017; 318(19): 1871-2.
- Reinhardt U. What Level of Health Spending Is “Affordable?” JAMA. 2017; 318(19): 1869-70.