Were QALYs invented in 1956?

On May 2 this year, the topic chosen by Tim Harford in his ‘Undercover economist‘ column in the Financial Times was ‘Healthcare: the final reckoning‘. Tim is always interesting, but I don’t find him sound on health care economics and I disagreed with much of what he said in his column. Others, including Jeff Round of UCL and Mark Sculpher from University of York have challenged his comments, and I’ll simply endorse their statements on substantive issues. But I was intrigued by the background that Tim used to introduce a description and critique of QALYs. Apparently “The Qaly was dreamt up in 1956 by two health economists, Christopher Cundell and Carlos McCartney.” Now, if that is true, then I do apologise to those two economists, or to their friends and families if they are no longer with us, for what I am about to say. But as someone who knows a bit about health economics and especially about QALYs, I found it mysterious that I had never heard of these inventors or of their act of inventing. Apart from which, my understanding has been that QALYs were not invented in a single act by one or more named individuals. Instead, several different sources, in different intellectual disciplines and traditions, have contributed to their development.

I shared my query about this on twitter, after which James Raftery from Southampton University and I both investigated where this invention claim came from. Using some variations in wording, it is to be found in many places on the web. But it was obvious that the original source for all of them was a Wikipedia article entitled ‘Quality-adjusted life year’. That article even had a citation for this claim, a review paper in a Serbian medical journal. It seemed to me to be unlikely that such a paper would actually have uncovered a fact about QALYs unknown to anyone else, and indeed the paper has no reference for its claim, just offering it as fact.

Adding to the mystery, the Wikipedia article actually claimed that three health economists had invented QALYs, including someone called “Toni Morgan”. Digging a little further, I found that the third inventor had been added relatively recently. Apologies to Toni if he or she is real and did help to invent QALYs, but I couldn’t help noticing that this name is an anagram of “Giant Moron” and may therefore be made up. The Serbian paper citation had also been added relatively recently, and that paper was published long after the original invention claim was made on Wikipedia. My conclusion is that the claim was originally made in the Wikipedia article; that was the unreferenced source for the same claim in the Serbian paper; and the Serbian paper was then added as a citation supporting the Wikipedia claim. This problem of circularity in the generation of fake facts is well-known, and Tim Harford, in acknowledging his error, pointed to this comic from xkcd:

citogenesis

It’s a lesson in how referencing and citation can go wrong. More digging shows that someone in the University of Ulster posted the original invented invention claim in December 2010, and the same or perhaps another wag at the same institution added the third name in February 2014. I guess they did it for the lulz. I am not too dismayed by the fact that no-one who knows anything about QALYs picked this spoof up for over three years, since such people should not really be using Wikipedia as a source. However, as Chris Sampson has suggested elsewhere on this blog, health economists should be paying more attention to what is published about their discipline on Wikipedia. Mis- or dis-information should be corrected or challenged.

I’m pleased to say that Don Husereau from the Institute of Health Economics in Canada has now fixed the Wikipedia entry and given a much more accurate and sensible history. Let’s hope that this is the last we hear of Christopher, Carlos and Toni. Unless of course they are real, in which case I hope their pioneering work gets the recognition that it deserves.

What does a health value of zero mean?

Submission from David Parkin

There’s a problem with the way that health economists and others describe the properties that a health state index should have.  The main reason we want such an index is to calculate Quality Adjusted Life Years.  So, we need the index’s possible values to run from zero to one, though we can also tolerate negative values.  But what does zero mean in this context?

There aren’t too many problems with saying what we mean by a health state that has a value of 1.  It’s described using terms like ‘full health’.  That’s interpreted to mean that one year spent in ‘full health’ will generate one Quality Adjusted Life Year.  1 QALY is as much health as any one person can have in a year.  There’s room for debate about what ‘full health’ means, in particular its subjective interpretation, but this is a detail about a coherent concept based on the idea of what a QALY is.

But it’s much more difficult to define what the value 0 means.  Health economics texts often define it as ‘dead’ or even ‘death’.  This is then followed by an explanation of what negative values mean, leading to the concept of ‘worse than dead’ or ‘worse than death’.  I think that this definition is wrong.  It’s misleading and may bias the results of health state valuation studies.

The most usual applications of the QALY model don’t aim to compare health states among the living with ‘being dead’.  They compare different health states amongst the living.  If 0 and 1 are intended to be health state values, they should be defined with respect to health states.  ‘Full health’ is a health state, but ‘being dead’ is not, except perhaps to zombies and vampires.  In fact, if you rate a dead person in EQ-5D health state terms, they will be a 33311.  Unable to do anything, but in no pain and not anxious or depressed.

Of course, it’s important that ‘dead’ is valued at 0.  ‘Full health’ must be valued at 1, because an essential QALY property is that every year of life spent in full health produces 1 QALY.  Similarly, ‘being dead’ must be valued at 0 because another essential QALY property is that dead people produce no QALYs.  But are there are other ways of producing no QALYs?

No QALYs are produced if there are no life years, but being dead is not even the only way to achieve that.  It can also be achieved by not being alive in the first place.  More importantly, a living person will also enjoy no QALYs in any year that they spend in health states that are valued at 0.  In the same way that the health state value 1 implies as much health that we can have at a given time, the health state value 0 implies a complete absence of health at a given time.  But what does that mean? They are not the worst health states that people can have, since to some people those worse states generate negative values.  So, what do health states with a value of 0 look like?

One way to solve this problem is to observe that they are health states that are as bad as being dead.  That gives us a way of thinking about them and of describing them to people for valuation studies.  This has an additional advantage.  It is more consistent with the idea of negative health values than is the idea that being dead defines zero. Negative values refer to levels of healthiness not deadness. It’s OK to describe health states with negative values as being worse than dead.  But that isn’t their essential feature, which is that they generate negative QALY values over time.  Negative numbers mean a very bad health state, not an extremely dead state.

Health state valuation studies in general use the term ‘dead’ for comparison with health states, explicitly or implicitly meaning 0.  But when being asked to value health states, can people really imagine ‘being dead’ in any meaningful way?  Some studies also use an even worse term, ‘death’.  The only route to being dead is to die.  But dead, dying and death are not the same things.  Dead is a state, though not a health state, but dying is a process and death an event.  Death and dying may be valued as negative in welfare terms even if dead is correctly valued at 0.  Using death as a comparison when valuing health states is likely to distort the values obtained.

Of course, many people recognise the issue that I’ve raised, but presumably they think that it is not important.  I think that it’s worth researching whether or not it matters empirically.  If not, I guess it’s a dead issue.