Menu Close
A man walking past closed shops

Why standard ways of valuing health were set aside during the pandemic

Governments around the world initially responded to COVID-19 according to the single most important aim: saving lives. But as the pandemic continued, affecting both health and finances, questions started arising as to what the right focus should be: protecting health or protecting the economy – or both. Implicitly, governments across the globe began considering a trade-off between the two in their decision making.

Making decisions on these matters is difficult. There is always more than one way to get things done. We call these alternatives or “competing measures”. When considering health and economic benefits, governments have had alternatives at their disposal at different levels: tight lockdowns versus less stringent ones (or none at all), open schools and universities versus online-only education, open versus closed borders, and so on.

Each alternative leads to both positive and negative consequences. Being able to select one requires answering difficult questions. How much more dip in the economy are we willing to accept for every life that would be saved with a lockdown? Or conversely, how many more deaths are we willing to accept in return for increased economic and other activities?

A standard practice for dealing with such difficult questions is to apply economic evaluation tools – measures that allow you to estimate the actual cost of efforts to protect people’s health, such as quality-adjusted life years (QALYs). Yet these haven’t been used.

How QALYs work

QALYs are a measure of how much good health an intervention provides. They measure not only the years of life saved by an intervention but also how disability-free those saved life years would be. A measure that gives one year of perfect health provides one QALY; if it provides a year of life that is compromised – say by a disability or chronic condition – then it provides only a fraction of a QALY.

One way the UK uses QALYs is in the NHS, to determine whether new and expensive treatments should be provided. QALYs make such decisions explicit and transparent. By estimating both the costs of the treatment and QALYs gained, you can judge whether it offers good value.

In the NHS, if the cost per QALY gained is between £20,000 and £30,000 (or up to £50,000 in case of some end-of-life treatments), the intervention is deemed cost-effective by the health watchdog, NICE. Other government departments also use QALYs, though they may use different thresholds depending on the specific context. The UK’s Department of Health and the Treasury use a higher threshold than the NHS, for example: £60,000 per QALY.

A patient on an intravenous drip in hospital
QALYs are often used to assess the value of medicines and other interventions to improve health. sfam_photo/Shutterstock

But despite their proven strength in making healthcare decisions explicit and transparent, QALYs haven’t been used by the UK government during the pandemic response. Researchers have estimated that each QALY saved through lockdowns, for example, may have cost the country hundreds of thousands or even millions of pounds.

These estimates are much higher than the traditional thresholds used by NICE and others. Why has this happened?

Not normal times

COVID-19 is an emergency. And one thing that differentiates emergencies from normal times is the high level of risk aversion that prevails due to uncertainties.

In an unfamiliar situation like a pandemic, the actual health impact of the problem is unknown. Calculating the scale of other impacts, such as economic harm, is also highly challenging because of the novelty of the situation. It’s very hard in such situations to calculate the scale of economic harm accurately.

In these sorts of situations, authorities tend to err on the side of caution. Experience shows that when so much is unknown, the desire to avoid the pandemic having a huge, uncontrollable health impact outweighs desires to assess the economic costs.

Plus, at multiple points during the pandemic, these unknowns haven’t been equal. The available hard data has shown not only frightening rates of viral transmission, but death rates soaring up and the threat of the NHS being overwhelmed. If the more concrete information in an uncertain situation points towards drastic consequences for people’s health, it’s not surprising that risk aversion kicks in and protecting health is prioritised over saving money.

For these reasons, despite calls for them to be used, cost-benefit measures such as QALYs have never been on the table. And as a result, rough calculations of the costs of saving a QALY have ended up being much higher than thresholds typically used in the UK.

Sadly, we are still in a highly uncertain situation without meaningful data on the wider impacts of different measures used to control the virus, beyond infection, hospitalisation and death rates. There are also additional factors, like the emergence of new variants of the coronavirus, that can quickly change the likely health impacts of the pandemic. Therefore, the application of normal times’ economic rules that govern healthcare decisions, although desirable, still isn’t feasible for the foreseeable future.

People queuing outside a UK vaccination centre
Modelling suggests that the cost of developing COVID vaccines is money well spent. Andy Rain/EPA-EFE

But what we should definitely be doing is collecting more hard data, retrospectively, on the economic and wider consequences of this crisis, so that we have more information at our disposal in future crises.

For example, although the cost per QALY saved wasn’t considered in developing or rolling out any of the COVID-19 vaccines, modelling suggests that vaccines appear to offer good value for money when considering the healthcare costs and deaths they avoid. Gathering information like this can help us build more robust economic models for situations down the line, and would help legitimise decisions on health spending in future pandemics.

Want to write?

Write an article and join a growing community of more than 182,100 academics and researchers from 4,941 institutions.

Register now