Public and private spending on health care has risen steadily worldwide over the past decades1. Take, for instance, the country where I live. In the Netherlands, the health care system is publicly funded through mandatory health insurance. The Dutch expenditure on health has increased at a higher rate than the gross national product2 in many of the past years, putting hospitals and insurance companies under pressure to reduce costs and curb this trend.

But what has given rise to these enormous increases in health care expenditures? Several causes have been identified3(in Dutch), such as ageing populations and extraordinary medical progress made in the past decades. In other words, we are living longer than our parents, and, if we become ill, treatments allow us to carry on our lives with a high quality of life. As a result, more people will depend on costly care, such as treatments for chronic diseases or long-term care for the elderly in nursing homes.

Paradoxical progress

Medical and pharmacological advancements are a double-edged sword. On the one hand, they have led to breakthroughs in the treatment of diseases for which no actual progress was made for decades, giving thousands of patients a chance of recovery they never dreamt of having. An example of such development is Orkambi®, a treatment for cystic fibrosis (CF). CF is a lung disease that leads to breathing complications, constant fatigue and vulnerability to illnesses. Patients with CF, mostly children, generally do not live beyond 40 years old and much of their time is spent on hospitals4. For CF patients who haven’t had any serious outlook for better treatments for years, Orkambi can realize a significant improvement.

On the other hand, creating drugs such as Orkambi costs money and time. As a result, new treatments put to market are often accompanied by shocking price tags. Orkambi, for example, was projected to cost a mere 180.000€ per patient per year*. Another example is Zolgensma, a gene therapy for a rare muscle disease, which costs more than 2 million euros per patient5.

When is it too expensive?

In countries with publicly funded health systems, such as the Netherlands or the United Kingdom, new treatments such as Orkambi go through a thorough evaluation before they become available to patients. Obviously, this evaluation involves determining the clinical benefits for patients (ineffective treatments are never funded). Furthermore, there is an economic evaluation, which assesses whether the treatment is worth its price. My research deals with some of the methods used in economic evaluation.

Determining if treatments are cost-effective is a sensitive process, as it deals with judging the value of health. Many people believe the value of health is infinite (‘you cannot put a price on human life’) and access to effective treatments is a human right6. In this perspective, cost should not dictate if treatments become available to patients, and it seems cruel even to conclude that a treatment that benefits patients is too expensive. To some extent, I agree with this position, at least on an emotional level. Denying treatment to patients, especially sick children, is undoubtedly undesirable and I feel that society should be willing to invest in improving access to treatment. Given that providing CF patients with Orkambi would require a minor investment per capita (e.g. 10€ per Dutch household each year could suffice**), who could look patients in the eye and tell them their treatment is too expensive?

Yet, a large part of society also considers expenditures on health insurance too high7 (in Dutch). Increasing health care premiums to cover the costs of treatments like Orkambi is likely to quickly evaporate the solidarity that is so crucial to publicly funded health systems. The alternative of shifting funds away from other valuable public goods, such as education, infrastructure or sustainability, also seems undesirable.

Hence, if the budget for pharmaceutics remains fixed, we need to spend it wisely. Stretching the budget for expensive treatments means that, at some point, we need to cut funding for other treatments or patients. In the wider context of health care funding, money might also be displaced from personnel costs (e.g. reducing the nursing staff per patient) or other factors related to the quality of care (e.g. management). In the end, we need to consider if what we gain by funding some treatments outweighs the losses incurred in other domains of care.

Furthermore, given that we can spend the budget only once, we could also consider what the health effects would be of spending the same value on treatments such as Orkambi in other sectors of care. Such analyses require comparing, for instance, how effective Orkambi is in improving children’s lung function and how effective bypass surgeries are for patients with heart disease. To do that, we need a measure of health.

Health on a scale

The QALY (quality-adjusted life year) has become one of the most popular measures of health. It considers not only how many life years are gained through treatment but also the quality of life in which these years are spent.

QALYs are calculated by multiplying gained life years by a quality of life weight, which has weight 0 for being dead and 1 for perfect health. Needing a wheelchair, for instance, would be given a weight smaller than 1, say 0.8. Each year in perfect health equals 1 QALY, and each year in a wheelchair equals 0.8 QALY. A treatment yielding a gain of ten years in perfect health and five in a wheelchair would thus generate 14 (10×1 + 0.8×5) QALYs per patient. By dividing the cost required to generate these QALYs, we can compare cost-effectiveness between treatments. For example, while Orkambi costs around 400.000€ per QALY*, treatment of cardiovascular disease requires around 40.000€ per QALY8 .

In some countries, such cost-effectiveness ratios are used as a tool for decision-making. In the Netherlands, for example, treatments that cost more than 80.000€ per QALY are not considered cost-effective***. By that standard, Orkambi is not worth its cost. However, making decisions based on costs per QALY raises important questions. First, what dictates the cost per QALY threshold (e.g. 80.000€)? Second, how do we weight the quality of life? Although the former is an interesting question in and of itself, the answer differs a lot between countries. In a nutshell, countries either opt to base it on what society believes a QALY is worth, or on the amount of money required to gain one QALY in the health care sector. Obviously, both approaches are complex and sensitive. My research, on the other hand, deals with the second question raised, i.e. finding out the value of quality of life.

The value of quality of life

The methods to calculate QALY weights mostly involve asking people to imagine living in a certain health state and making choices between hypothetical scenarios (e.g. living shorter in full health or taking some risk of immediate death). In that context, it becomes crucial to understand how people make such complex decisions about health.

From my PhD studies on health decisions, I have found that people are usually loss averse; they are much more motivated by avoiding losses than in realizing gains in health. Also, people generally feel that their next few years of life matter more than years in the further future. Importantly, individuals’ choices in such scenarios may differ, depending on their expectations about the length of life and on how and when they are asked to make such a choice.

In contrast, when measuring QALYs, we often assume that people are perfectly rational and consistent because that makes calculating QALY weights easier. This simplifying approach, however, means that we impose invalid assumptions about how people think about health. For example, we assume that everyone considers each year worth exactly the same as the next. This also means that avoiding a loss of a year of life is the same as gaining a year of life. So far, the methodology to address these issues was lacking. Together with my supervisors, I have incorporated some of these psychological insights into decisions about health within the process of determining the value of quality of life.

What did we do? We measured how each person decides about health and included these criteria in how we calculate QALY weights. In essence****, we tried to find out how averse to losing health people are, and whether they feel that the value of their years changes over time. We incorporated this individual information into the calculation of QALY weights, a process we call ‘the corrective approach’9.

With my research, I hope to bring the methods we use to determine the cost-effectiveness of treatments such as Orkambi closer to how we actually decide about health. As I discussed earlier, on an emotional level, I wish no patient was ever denied access to treatments, regardless of the costs involved. However, if we accept the reality that, at some point, some treatments may be too expensive, I hope that my research at least allows us to make such decisions being more confident in the underlying methodology.

* As published by the Dutch Health Care Institute
** Providing all patients with Orkambi would cost around 80 million€, and the Netherlands has almost 8 million households
*** See the following documentation by the Dutch Health Care Institute
**** This was a highly technical process; the paper reporting it will come out in Health Economics published as Open Access soon.

Share your Science
The Share your Science section aims at giving students and researchers a space to share their thesis to a broader audience. UA Magazine wants to increase the visibility of recent academic work and serve as a bridge between universities and societies.
How do we decide about our health? For Stefan Lipman, this question is core to his research, teaching, and train of thought. He is mainly interested in finding answers to this question by combining insights from health economics, behavioral economics, and psychology. Stefan studied social and health psychology and is currently a Ph.D. candidate at Erasmus University Rotterdam. Most of his work has focused on risk and time preference for health, valuation of health and quality of life, and understanding healthy habits.


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