Are QALYs #ableist?

As many of us who have had to review submitted journal articles, thesis defenses, grant applications, white papers, and even published literature know, providing feedback on something that is poorly conceived is much harder than providing feedback on something well done.

This is going to be hard.

Who is ValueOurHealth?

The video above comes from the website of “ValueOurHealth.org”; I would tell you more about them, but there is no “About Us” menu item on the website. However, the website indicates that they are a group of patient organizations concerned about:

“The use of flawed, discriminatory value assessments [that] could threaten access to care for patients with chronic illnesses and people with disabilities.”

In particular, who find issue with value assessments that

“place a value on the life of a human based on their health status and assume every patient will respond the same way to treatments.”

QALYs, according to these concerned patient groups, assign a value to human beings. People with lower values (like Jessica, in the video above), then, will be denied coverage because their life is “valued less than someone in perfect health” which means “less value is also placed on treating” them. (Many will be quick to notice that health states and QALYs are used interchangeably here. I try to explain why below.)

It’s not like this is a well-intended rogue group who simply misunderstands the concept of a QALY, requires someone to send them a polite email, and then we can all move on. Other groups have also asserted that QALYs unfairly discriminate against the aged and disabled, and include AimedAlliance, Alliance for Patient Access, Institute for Patient Access, Alliance for Aging Research, and Global Liver Institute. There are likely many more patient groups that abhor QALYs (and definite articles/determiners, it seems) out there, and are justifiably concerned about patient access to therapy. But these are all the ones I could find through a quick search and sitting from my perch in Canada.

Why do they hate QALYs?

One can infer pretty quickly that ValueOurHealth and their illustrative message is largely motivated by another very active organization, the “Partnership to Improve Patient Care” (PIPC). The video, and the arguments about “assigning QALYs” to people, seem to stem from a white paper produced by the PIPC, which in turn cites a very nicely written paper by Franco Sassi (of Imperial College London), that explains QALY and DALY calculations for researchers and policymakers.

The PIPC white paper, in fact, uses the very same calculation provided by Prof. Sassi to illustrate the impact of preventing a case of tuberculosis. However, unlike Prof. Sassi’s illustrative example, the PIPC fails to quantify the QALYs gained by the intervention. Instead they simply focus on the QALYs an individual who has tuberculosis for 6 months will experience. (0.36, versus 0.50, for those keeping score). After some further discussion about problems with measuring health states, the PIPC white paper then skips ahead to ethical problems with QALYs central to their position, citing a Value in Health paper by Erik Nord and colleagues. One of the key problems with the QALY according to the PIPC and argued in the Nord paper goes as follows:

“Valuing health gains in terms of QALYs means that life-years gained in full health—through, for instance, prevention of fatal accidents in people in normal health—are counted as more valuable than life-years gained by those who are chronically ill or disabled—for instance, by averting fatal episodes in people with asthma, heart disease, or mental illness.”

It seems the PIPC assume the lower number of QALYs experienced by those who are sick equates with the value of lives to payers. Even more interestingly, Prof. Nord’s analysis says nothing about costs. While those who are older have fewer QALYs to potentially gain, they also incur fewer costs. This is why, contrary to the assertion of preventing accidents in healthy people, preventive measures may offer a similar value to treatments when both QALYS and costs are considered.

It is also why an ICER review showed that alemtuzumab is good value in individuals requiring second-line treatment for relapse-remitting multiple sclerosis (1.34 QALYs can be gained compared to the next best alternative and at a lower cost then comparators), while a policy of annual mammography screening of similarly aged (i.e., >40) healthy women is of poor economic value (0.036 QALYs can be gained compared to no screening at an additional cost of $5,500 for every woman). Mammography provides better value in older individuals. It is not unlike fracture prevention and a myriad of other interventions in healthy, asymptomatic people in this regard. Quite contrary to the assertion of these misinformed groups, many interventions represent increasingly better value in frail, disabled, and older patients. Relative risks create larger yields when baseline risks are high.

None of this is to say that QALYs (and incremental cost-effectiveness ratios) do not have problems. And the PIPC, at the very least, should be commended for trying to advance alternative metrics, something that very few critics have offered. Instead, the PIPC and like-minded organizations are likely trapped in a filter bubble. They know there are problems with QALYs, and they see expensive and rare disease treatments being valued harshly. So, ergo, blame the QALY. (Note to PIPC: it is because the drugs are expensive, relative to other life-saving things, not because of your concerns about the QALY.) They then see that others feel the same way, which means their concerns are likely justified. A critique of QALYs issued by the Pioneer Institute identifies many of these same arguments. One Twitterer, a disabled Massachusetts lawyer “alive because of Medicaid” has offered further instruction for the QALY-naive.

What to do about it?

As a friend recently told me, not everyone is concerned with the QALY. Some don’t like what they see as a rationing approach promoted by the Institute for Clinical and Economic Review (ICER) assessments. Some hate the QALY. Some hate both. Last year, Joshua T. Cohen, Dan Ollendorf, and Peter Neumann published their own blog entry on the effervescing criticism of ICER, even allowing the PIPC head to have a say about QALYs. They then tried to set the record straight with these thoughts:

While we applaud the call for novel measures and to work with patient and disability advocates to understand attributes important to them, there are three problems with PIPC’s position.

First, simply coming up with that list of key attributes does not address how society should allocate finite resources, or how to price a drug given individual or group preferences.

Second, the diminished weight QALYs assign to life with disability does not represent discrimination. Instead, diminished weight represents recognition that treatments mitigating disability confer value by restoring quality of life to levels typical among most of the population.

Finally, all value measures that inform allocation of finite resources trade off benefits important to some patients against benefits potentially important to others. PIPC itself notes that life years not weighted for disability (e.g., the equal value life-year gained, or evLYG, introduced by ICER for sensitivity analysis purposes) do not award value for improved quality of life. Indeed, any measure that does not “discriminate” against patients with disability cannot award treatments credit for improving their quality of life. Failing to award that credit would adversely affect this population by ruling out spending on such improvements.

Certainly a lot more can be said here.

But for now, I am more curious what others have to say…

My quality-adjusted life year

Why did I do it?

I have evaluated lots of services and been involved in trials where I have asked people to collect EQ-5D data. During this time several people have complained to me about having to collect EQ-5D data so I thought I would have a ‘taste of my own medicine’. I measured my health-related quality of life (HRQoL) using EQ-5D-3L, EQ-5D-VAS, and EQ-5D-5L, every day for a year (N=1). I had the EQ-5D on a spreadsheet on my smartphone and prompted myself to do it at 9 p.m. every night. I set a target of never being more than three days late in doing it, which I missed twice through the year. I also recorded health-related notes for some days, for instance, 21st January said “tired, dropped a keytar on toe (very 1980s injury)”.

By doing this I wanted to illuminate issues around anchoring, ceiling effects and ideas of health and wellness. With a big increase in wearable tech and smartphone health apps this type of big data collection might become a lot more commonplace. I have not kept a diary since I was about 13 so it was an interesting way of keeping track on what was happening, with a focus on health. Starting the year I knew I had one big life event coming up: a new baby due in early March. I am generally quite healthy, a bit overweight, don’t get enough sleep. I have been called a hypochondriac by people before, typically complaining of headaches, colds and sore throats around six months of the year. I usually go running once or twice a week.

From the start I was very conscious that I felt I shouldn’t grumble too much, that EQ-5D was mainly used to measure functional health in people with disease, not in well people (and ceiling effects were a feature of the EQ-5D). I immediately felt a ‘freedom’ of the greater sensitivity of the EQ-5D-5L when compared to the 3L so I could score myself as having slight problems with the 5L, but not that they were bad enough to be ‘some problems’ on the 3L.

There were days when I felt a bit achey or tired because I had been for a run, but unless I had an actual injury I did not score myself as having problems with pain or mobility because of this; generally if I feel achey from running I think of that as a good thing as having pushed myself hard, ‘no pain no gain’. I also started doing yoga this year which made me feel great but also a bit achey sometimes. But in general I noticed that one of the main problems I had was fatigue which is not explicitly covered in the EQ-5D but was reflected sometimes as being slightly impaired on usual activities. I also thought that usual activities could be impaired if you are working and travelling a lot, as you don’t get to do any of the things you enjoy doing like hobbies or spending time with family, but this is more of a capability question whereas the EQ-5D is more functional.

How did my HRQoL compare?

I matched up my levels on the individual domains to EQ-5D-3L and 5L index scores based on UK preference scores. The final 5L value set may still change; I used the most recent published scores. I also matched my levels to a personal 5L value set which I did using this survey which uses discrete choice experiments and involves comparing a set of pairs of EQ-5D-5L health states. I found doing this fascinating and it made me think about how mutually exclusive the EQ-5D dimensions are, and whether some health states are actually implausible: for instance, is it possible to be in extreme pain but not have any impairment on usual activities?

Surprisingly, my average EQ-5D-3L index score (0.982) was higher than the population averages for my age group (for England age 35-44 it is 0.888 based on Szende et al 2014); I expected them to be lower. In fact my average index scores were higher than the average for 18-24 year olds (0.922). I thought that measuring EQ-5D more often and having more granularity would lead to lower average scores but it actually led to high average scores.

My average score from the personal 5L value set was slightly higher than the England population value set (0.983 vs 0.975). Digging into the data, the main differences were that I thought that usual activities were slightly more important, and pain slightly less important, than the general population. The 5L (England tariff) correlated more closely with the VAS than the 3L (r2 =0.746 vs. r2 =0.586) but the 5L (personal tariff) correlated most closely with the VAS (r2 =0.792). So based on my N=1 sample, this suggests that the 5L is a better predictor of overall health than the 3L, and that the personal value set has validity in predicting VAS scores.

Figure 1. My EQ-5D-3L index score [3L], EQ-5D-5L index score (England value set) [5L], EQ-5DL-5L index score (personal value set) [5LP], and visual analogue scale (VAS) score divided by 100 [VAS/100].

Reflection

I definitely regretted doing the EQ-5D every day and was glad when the year was over! I would have preferred to have done it every week but I think that would have missed a lot of subtleties in how I felt from day to day. On reflection the way I was approaching it was that the end of each day I would try to recall if I was stressed, or if anything hurt, and adjust the level on the relevant dimension. But I wonder if I was prompted at any moment during the day as to whether I was stressed, had some mobility issues, or pain, would I say I did? It makes me think about Kahneman and Riis’s ‘remembering brain’ and ‘experiencing brain’. Was my EQ-5D profile a slave to my ‘remembering brain’ rather than my ‘experiencing brain’?

One thing when my score was low for a few days was when I had a really painful abscess on my tooth. At the time I felt like the pain was unbearable so had a high pain score, but looking back I wonder if it was that bad, but I didn’t want to retrospectively change my score. Strangely, I had the flu twice in this year which gave me some health decrements, which I don’t think has ever happened to me before (I don’t think it was just ‘man flu’!).

I knew that I was going to have a baby this year but I didn’t know that I would spend 18 days in hospital, despite not being ill myself. This has led me to think a lot more about ‘caregiver effects‘ – the impact of close relatives being ill; it is unnerving spending night after night in hospital, in this case because my wife was very ill after giving birth, and then when my baby son was two months old, he got very ill (both are doing a lot better now). Being in hospital with a sick relative is a strange feeling, stressful and boring at the same time. I spent a long time staring out of the window or scrolling through Twitter. When my baby son was really ill he would not sleep and did not want to be put down, so my arms were aching after holding him all night. I was lucky that I had understanding managers in work and I was not significantly financially disadvantaged by caring for sick relatives. And glad of the NHS and not getting a huge bill when family members are discharged from hospital.

Health, wellbeing & exercise

Doing this made me think more about the difference between health and wellbeing; there might be days where I was really happy but it wasn’t reflected in my EQ-5D index score. I noticed that doing exercise always led to a higher VAS score – maybe subconsciously I was thinking exercise was increasing my ‘health stock‘. I probably used the VAS score more like an overall wellbeing score rather than just health which is not correct – but I wonder if other people do this as well, and that is why there are less pronounced ceiling effects with the VAS score.

Could trials measure EQ-5D every day?

One advantage of EQ-5D and QALYs over other health outcomes is that they should be measured over a schedule and use the area under the curve. Completing an EQ5D every day has shown me that health does vary every day, but I still think it might be impractical for trial participants to complete an EQ-5D questionnaire every day. Perhaps EQ-5D data could be combined with a simple daily VAS score, possibly out of ten rather than 100 for simplicity.

Joint worst day: 6th and 7th October: EQ-5D-3L index 0.264, EQ-5D-5L index 0.724; personal EQ-5D-5L index 0.824; VAS score 60 – ‘abscess on tooth, couldn’t sleep, face swollen’.

Joint best day: 27th January, 7th September, 11th September, 18th November, 4th December, 30th December: EQ-5D-3L index 1.00;  both EQ-5D-5L index scores 1.00; VAS score 95 – notes include ‘lovely day with family’, ‘went for a run’, ‘holiday’, ‘met up with friends’.

IVF and the evaluation of policies that don’t affect particular persons

Over at the CLAHRC West Midlands blog, Richard Lilford (my boss, I should hasten to add!) writes about the difficulties with the economic evaluation of IVF. The post notes that there are a number of issues that “are not generally considered in the standard canon for health economic assessment” including the problems with measuring benefits, choosing an appropriate discount rate, indirect beneficiaries, and valuing the life of the as yet unborn child. Au contraire! These issues are the very bread and butter of health economics and economic evaluation research. But I would concede that their impact on estimates of cost-effectiveness are not nearly well enough integrated into standard assessments.

We’ve covered the issue of choosing a social discount rate on this blog before with regards to treatments with inter-generational effects. I want instead to consider the last point about how we should, in the most normative of senses, consider the life of the child born as a result of IVF.

It puts me in mind of the work of the late, great Derek Parfit. He could be said to have single-handedly developed the field of ethics about future people. He identified a number of ethical problems that still often don’t have satisfactory answers. Decisions like funding IVF have an impact on the very existence of persons. But these decisions do not affect the well-being or rights of any particular persons, rather, as Parfit terms them, general persons. Few would deny that we have moral obligations not to cause material harm to future generations. Most would reject the narrow view that the only relevant outcomes are those that affect actual, particular persons, the narrow person-centred view. For example, in considering the problem of global warming, we do not reject its consequences on future generations as being irrelevant. But there remains the question about how we morally treat these general, future persons. Parfit calls this the non-identity problem and it applies neatly to the issue of IVF.

To illustrate the problem of IVF consider the choice:

If we choose A Adam and Barbara will not have children Charles will not exist
If we choose B Adam and Barbara will have a child Charles will live to 70

If we ignore evidence that suggests quality of life actually declines after one has children, we will assume that Adam and Barbara having children will in fact raise their quality of life since they are fulfilling their preferences. It would then seem to be clear that the fact of Charles existing and living a healthy life would be better than him not existing at all and the net benefit of Choice B is greater. But then consider the next choice:

If we choose A Adam and Barbara will not have children Charles will not exist Dianne will not exist
If we choose B Adam and Barbara will have a child Charles will live to 70 Dianne will not exist
If we choose C Adam and Barbara will have children Charles will live to 40 Dianne will live to 40

Now, Choice C would still seem to be preferable to Choice B if all life years have the same quality of life. But we could continue adding children with shorter and shorter life expectancies until we have a large population that lives a very short life, which is certainly not a morally superior position. This is a version of Parfit’s repugnant conclusion, in which general utilitarian principles leads us to prefer a situation with a very large, very low quality of life population to a smaller, better off one. No satisfying solution has yet been proposed. For IVF this might imply increasing the probability of multiple births!

We can also consider the “opposite” of IVF, contraception. In providing contraception we are superficially choosing Choice A above, which by the same utilitarian reasoning would be a worse situation than one in which those children are born. However, contraception is often used to be able to delay fertility decisions, so the choice actually becomes between a child being born earlier and living a worse life than a child being born later in better circumstances. So for a couple, things would go worse for the general person who is their first child, if things are worse for the particular person who is actually their first child. So it clearly matters how we frame the question as well.

We have a choice about how to weigh up the different situations if we reject the ‘narrow person-centred view’. On a no difference view, the effects on general and particular persons are weighted the same. On a two-tier view, the effects on general persons only matter a fraction of those on particular persons. For IVF this relates to how we weight Charles’s (and Diane’s) life in an evaluation. But current practice is ambiguous about how we weigh up these lives, and if we have a ‘two-tier view’, how we weight the lives of general persons.

From an economic perspective, we often consider that the values we place on benefits resulting from decisions as being determined by societal preferences. Generally, we ignore the fact that for many treatments the actual beneficiaries do not yet exist, which would suggest a ‘no difference view’. For example, when assessing the benefits of providing a treatment for childhood leukaemia, we don’t value the benefits to those particular children who have the disease differently to those general persons who may have the disease in the future. Perhaps we do not consider this since the provision of the treatment does not cause a difference in who will exist in the future. But equally when assessing the effects of interventions that may cause, in a counterfactual sense, changes in fertility decisions and the existence of persons, like social welfare payments or a lifesaving treatment for a woman of childbearing age, we do not think about the effects on the general persons that may be a child of that person or household. This would then suggest a ‘narrow person-centred view’.

There is clearly some inconsistency in how we treat general persons. For IVF evaluations, in particular, many avoid this question altogether and just estimate the cost per successful pregnancy, leaving the weighing up of benefits to later decision makers. While the arguments clearly don’t point to a particular conclusion, my tentative conclusion would be a ‘no difference view’. At any rate, it is an open question. In my rare lectures, I often remark that we spend a lot more time on empirical questions than questions of normative economics. This example shows how this can result in inconsistencies in how we choose to analyse and report our findings.

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