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Discrimination, Triage and Denial-of-
Treatment: Lessons from COVID-19 in
the UK*
Wayne Martin
1. Squash the Sombrero
In a recent report by Amnesty International, the son of one care home resident in
Cumbria (UK) reported on his father’s experience during the COVID-19 pandemic:
From day one, the care home was categoric it was probably COVID and he
would die of it and he would not be taken to hospital. He only had a cough
at that stage. He was only 76 and was in great shape physically. He loved to
go out and it would not have been a problem for him to go to hospital. The
care home called me and said he had symptoms, a bit of a cough and that
doctor had assessed him over mobile phone and he would not be taken to
hospital. Then I spoke to the GP later that day and said he would not be
taken to hospital but would be given morphine if in pain. Later he collapsed
on the floor in the bathroom and the care home called the paramedic who
established that he had no injury and put him back to bed and told the
carers not to call them back for any COVID-related symptoms because they
would not return. He died a week later.1
Based on this report and others like it, Amnesty concluded that the UK Government
violated the human rights of care home residents, including the right to life and the right
to the highest attainable standard of health. Amnesty does not use the word ‘torture’ in
their report, but they do conclude that “[t]hese decisions and policies … may have
violated their right not to be subjected to inhuman or degrading treatment.”2
What lessons might be learned from the UK’s practice of treatment-denial during the
first wave of the coronavirus pandemic? In order to tackle this question, we need to
reconstruct the policy environment, and the policy imperatives, that shaped the UK’s
response. In doing so, we can begin from a now-famous press conference at No 10
* A number of colleagues and friends provided helpful comments on earlier drafts of this paper.
Among them I would like to thank in particular: Neil Allen, Jason Coppel, Amita Dhanda, Beatrice Han-
Pile, Emily Fitton, Alex Ruck Keene, Margot Kuylen, Sabine Michalowski, Daniel Watts and Aaron Wyllie.
Research support was provided by Beatrice Carniato. Early versions of the paper were presented to the
Essex Explores lecture series and at a webinar organised by Validity. I am grateful to the organisers and
participants at these two events. Support for the research presented in this paper was provided by the
Arts and Humanities Research Council under the UKRI COVID-19 Rapid Response funding scheme.
Grant number: AH/V012770/1 (Ensuring Respect for Human Rights in Locked-Down Care Homes).
1 Amnesty International, ‘As if Expendable: The UK Government’s Failure to Protect Older People
in Care Homes During the COVID-19 Pandemic’ (
Amnesty International
2020) 22.
2 ibid 5-6.
23
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Downing Street on 12 March, 2020. British Prime Minister Boris Johnson there
introduced his subsequently much-repeated catch-phrase:
Squash the Sombrero.
The
expression referred to a graph that was displayed at the press conference. (See Fig. 1.).
The graph plotted two curves. The first, labelled “No action” had a shape reminiscent of
a traditional Mexican hat. It projected a sharp rise in COVID cases in the UK through
the Spring of 2020, followed by a sharp tapering off. The second line, labelled “With the
action proposed,” showed a slower rise to a lower peak over a longer period. In the
Government’s graph there was also a third line, labelled “NHS Surge Capacity,”
representing the maximum number of cases that could be accommodated by the NHS
(National Health Service) at any given time.3While the first line (“No action”) rose far
above surge capacity, the second line, in which the sombrero was ‘squashed’, represented
the total number of cases as topping out just within the total capacity that the health
system could handle.
Boris Johnson’s graph, and its accompanying catchphrase, quickly spread all over the
world. It also occasioned controversy. Four days later, the COVID-19 Response Team at
University College London (UCL) published its own graph, in a paper signed by 30 co-
authors.4(See Fig. 2.).
3 In the health policy literature, the term ‘surge capacity’ is defined as “the ability to manage a sud-
den, unexpected increase in patient volume that would otherwise severely challenge or exceed the present
capacity.” J Hick and others, ‘Health Care Facility and Community Strategies for Patient Care Surge
Capacity’ (2004) 44.3 Annals of Emergency Medicine 254.
4 N Ferguson and others, ‘Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19
mortality and healthcare demand’ (Imperial College COVID-19 Response Team; 16 March, 2020)
<https://doi.org/10.25561/77482> accessed 8 December 2020.
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Tackling Torture: Victims with Disabilities in the COVID-19 Outbreak
Figure 1: HM Government, 'Profile of the Epidemic under Different Approaches' Press Briefing, 10
Downing St., (12 March 2020).
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The UCL graph also included an alarming “Sombrero-shaped” curve, together with four
further curves with lower peaks, modelling a variety of different policy interventions.
Crucially, however, none of the UCL curves managed to stay under the line representing
surge critical care bed capacity – a line which hovered disturbingly close to the x-axis.
Even the lowest of the UCL curves peaked at nine times NHS critical care capacity. The
UCL paper was one of a number of reports that understandably spread alarm among
those with responsibility for managing frontline emergency services. It also raised a
policy question to which there are no comfortable answers:
How should the health
services respond to a situation in which demand for live-saving interventions massively
swamps supply?
For the purposes of the present discussion, I refer to such circumstances
as
triage situations
.5
How can triage situations be managed in a way that is respectful of human rights?6One
response to this question was offered only a few days later, in a joint statement signed
by over 60 officials associated with the UN human rights system. Published by the Office
5 My use of this expression is somewhat idiosyncratic, both because there are some forms of
triage that do not pertain to life-saving interventions and because (as we shall see) there are some re-
sponses to such situations that avoid recourse to triage.
6 In tackling this question, I am building upon the initial survey of these issues in S Michalowski
and others, ‘Triage in the COVID-19 Pandemic: Bioethical and Human Rights Considerations’ (University
of Essex: Joint Technical Report of the Essex Autonomy Project and the Ethics of Powerlessness Project, 6
April, 2020); <http://doi.org/10.13140/RG.2.2.34046.74567> accessed 8 June 2020. For a discussion of
human rights issues raised by the use of age as a triage condition, see: S Michalowski, ‘The Use of Age as
a Triage Condition’ in C Ferstman and A Fagan, (eds.)
Covid-19, Law and Human Rights
(University of
Essex: Essex Dialogues), 93–100 <http://repository.essex.ac.uk/id/eprint/28027> accessed 26 September
2020.
25
Tackling Torture: Victims with Disabilities in the COVID-19 Outbreak
Figure 2: Ferguson et al, ‘Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19
mortality and healthcare demand.’ Imperial College COVID-19 Response Team (16 March 2020);
<https://doi.org/10.25561/77482> accessed 25 November 2020.
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of the High Commission for Human Rights, the statement delivered its main message
already in its headline: “Everyone has the right to life-saving interventions.”7The body
of the statement went on to elaborate the point as follows:
Everyone, without exception, has the right to life-saving interventions and
this responsibility lies with government. The scarcity of resources… should
never be a justification to discriminate against certain groups of patients.
Everybody has the right to health.8
We shall have occasion to return to this UN statement below. But it is important to
appreciate the difficulty that it creates for those on the frontline. Put yourself in the
position of a manager of an intensive care unit, or the chair of the ethics committee at
the hospital where that unit is located. Your immediate and daunting task is to prepare
for a situation where there simply are not enough life-saving interventions to go around.
The UN statement reminds you that everyone has a right to life-saving interventions.
No exceptions
. But if anything, this only serves to make your problem worse. If demand
swamps supply, then not only will you fail to meet patients’ medical needs; in doing so
you will be violating the human rights of some patients in order to fulfil the rights of
others. So whose rights should you prioritise?
2. The British Triage System
Faced with the tragedy of a triage situation, one overarching principle sounds appealing
– perhaps even obvious.
If we cannot save everyone then we should at least save as many
lives as possible.
This intuitively attractive idea is the animating principle of what is
known in the bioethics literature as
the British triage system
– so-called not because its
use is confined to the British but because it was first formulated and operationalised by
the British Navy in the 19th century.9In its original military setting, the strategy was to
withhold critical medical resources both from those with “slight injuries” and from those
whose injuries are “likely to prove fatal” in order to channel those resources to those in
a third category: those who are “seriously injured.” In this context, the seriously injured
are understood to be those for whom the intervention is most likely
to make the vital
difference
– i.e., the difference between living and dying.10
The British triage system provides what I shall refer to as a
meta-schema
for the
management of triage situations. That is, it provides an overarching policy framework
for the distribution of life-saving medical interventions, but by itself it does not suffice
to guide practice. In order to do so, it needs to be
specified and operationalised
for
application to the circumstances of the public health emergency at hand. In planning
7 United Nations Office of the High Commissioner for Human Rights, “No Exceptions with
COVID-19: ‘Everyone has the rights to life-saving interventions’ – UN Experts Say”;
<www.ohchr.org/EN/NewsEvents/Pages/DisplayNews.aspx?NewsID=25746> accessed 24 May 2020.
8 ibid.
9 On the difference between French and British approaches to triage in the 19th century, see: J
Kirby, ‘Enhancing Fairness in Pandemic Triage’ (2010) 36:12 Journal of Medical Ethics 758; N Okorie, ‘Par-
tiality, Impartiality and the Ethics of Triage’ (2019) 19 Developing World Bioethics 80.
10 For the canonical statement of this approach, see J Wilson,
Outlines of Naval Surgery
(McLach-
lan, Stewart and Co 1846), ch. 3. For a discussion see, J Watt, ‘Doctors in the Wars’ (1984) 77 Journal of the
Royal Society of Medicine 265.
26
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for the anticipated triage situation in the first wave of COVID-19, that meant translating
the meta-schema into a concrete plan for prioritising the allocation of intensive care
resources (ICU beds, ICU staff, emergency equipment and supplies such as ventilator
units and oxygen…) in light of emerging data about which lives were most likely to be
saved by deploying them.
In probing the issues raised by the meta-schema, my strategy here will be to consider in
detail one controversial specification and operationalisation of it that was developed
during the first wave of the pandemic. (See Fig. 3.).
The COVID-19 Decision Support Tool was prominently ‘branded’ as NHS, and was
included in the
Electronic Clinical Handbook
of at least one NHS trust.11 Nonetheless,
its use was never formally authorised or endorsed by the NHS itself; indeed, NHS England
ultimately issued a statement distancing itself from the tool.12 For our purposes here, the
11 NHS Dumfries and Galloway Electronic Clinical Handbook <www.nhsdghandbook.co.uk/wp-
content/uploads/2020/04/COVID-Decision-Support-Tool.pdf> accessed 9 December 2020.
12 According to the NHS statement: “The decision-making guidance… derived from work commis-
sioned from an expert group for consideration by Government, which was subsequently stood down on
28/29 March 2020, without DHSC or NHS implementation, after a review of capacity and pandemic tra-
jectory.
It therefore remained in draft and unpublished
.” NHS England, ‘NHS and Other Professional Bod-
ies’ Response to the Sunday Times’ 25 October 2020 <www.england.nhs.uk/2020/10/nhs-and-
other-professional-bodies-response-to-sunday-times> accessed 9 December 2020 (emphasis added). The
statement quotes the co-chair of one national NHS ethics committee: “We were asked to look at the issue
of a Covid-19 triage tool, however, it wasn’t needed” (ibid).
27
Tackling Torture: Victims with Disabilities in the COVID-19 Outbreak
Figure 3: COVID-19 Decision Support Tool;
NHS Dumfries and Galloway Handbook
;
<https://www.nhsdghandbook.co.uk/wp-content/uploads/2020/04/COVID-Decision-Support-
Tool.pdf> accessed 9 December 2020.
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Decision Support Tool provides a useful focus for analysis, as it shines a light on some
of the finer grain of triage planning and brings some of the key human rights challenges
into sharp relief.
The Decision Support Tool operates with a points-based system. Patients with 8 points
or fewer are prioritised for ICU admission; those with more than 8 points are directed
to care outside an ICU setting, and in the limiting case offered only palliative
interventions. Points are allocated in part based on age (with older patients given more
points), co-morbidity, gender (women were given a one-point ‘discount’), and ‘frailty.’
The rationale of the tool was to direct ICU treatment towards those who, based on the
emerging epidemiological data about mortality rates, were most likely to survive in a
COVID ICU setting. Because patients who were older, frailer, ill or male were showing
lower survival rates in such settings,13 the decision tool made it less likely for them to
receive ICU treatment.
In considering the inner workings of the Decision Tool, we need to pause over the so-called
“Clinical Frailty Index” (or “Rockwood Frailty Scale”) that lies at its core. (See Fig. 4.).
13 UK Office for National Statistics, ‘Deaths Involving COVID-19, England and Wales: Deaths
Occurring in March 2020’; <www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriage-
s/deaths/bulletins/deathsinvolvingcovid19englandandwales/deathsoccurringinmarch2020> accessed 24
November 2020.
28
Tackling Torture: Victims with Disabilities in the COVID-19 Outbreak
Figure 4: Rockwood Clinical Frailty Scale; NHS Specialised Clinical Frailty Network, “Frailty & COVID-
19: Why, What, How, Where & When?”; <https://www.scfn.org.uk/clinical-frailty-scale> accessed 22
November 2020.
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Originally developed by Rockwood and colleagues in the context of a large Canadian
study,14the Frailty Index in its current form comprises a nine-point scale ranging from 1
(“Very Fit”) to 9 (“Terminally Ill”). Each point on the scale is elaborated with a short
descriptor combined with a prototypical silhouetted figure. The scale is itself a well-
established tool within the NHS, and is endorsed by the NHS Clinical Frailty Network as
“a reliable predictor of outcomes in the urgent care context.”15 Its validity has been
established on the basis of a number of studies; for example, data from one longitudinal
study demonstrated a striking correlation between frailty score and mortality rates over
an 800-day period.16 (See Fig. 5.).
For our purposes, it is worth taking note of the descriptor associated with the midpoint
score on the scale:
5. Mildly Frail: These people often have more evident slowing, and need
help in high order IADLs [Independent Activities of Daily Life] (finances,
transportation, heavy housework, medications). Typically, mild frailty
progressively impairs shopping and walking outside alone, meal
preparation and housework.17
14 K Rockwood and others, ‘A Global Clinical Measure of Fitness and Frailty in Elderly People’
(2005) 173:5 Canadian Medial Association Journal 489.
15 NHS Specialised Clinical Frailty Network, ‘Frailty & COVID-19: Why, What, How, Where &
When?’ <www.scfn.org.uk/clinical-frailty-scale> accessed 22 November 2020.
16 ibid.
17 ibid.
29
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Figure 5: Frailty Scale Scores as Predictor of Mortality Rates; adapted from NHS Specialised Clinical
Frailty Network; <https://www.scfn.org.uk/clinical-frailty-scale> accessed 25 November 2020; image
credit: Beatrice Carniato.
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Consider how this applies to someone in the position of the care-home resident in
Cumbria. As a resident of a care home, it is safe to assume that he requires support in his
‘IADLs’. So he would score a minimum of 5 on the frailty scale. His son describes him “in
great shape physically,” so let’s assume he scores zero on co-morbidity. But he is 76-years
old, so the Decision Support Tool assigns him another five points for age. That gives him
a
minimum of ten points
on the Decision Support Tool, where a score of 8 is the threshold
for eligibility for ICU care. And as we know from his son’s testimony to Amnesty, he was
in fact denied admission to an ICU unit, or even to a hospital ward, and was offered
palliative care only (in the form of morphine for pain relief) in the care home setting.
3. Three Levels of Controversy
The COVID-19 Decision Support Tool proved to be intensely controversial;18 indeed by
mid-April NHS England had denounced it. A statement to the press made clear that
“[a]ny individual clinician choosing to use this [tool] is doing so against the clear advice
of NHS England.”19 So what was the problem with the Support Tool and what lessons
can we learn from its failure? For the purposes of our analysis it will be useful to
distinguish three distinct levels or categories of concern: (i) concerns about use of the
Frailty Index itself; (ii) concerns about the COVID Decision-Tool within which the
Frailty Index was embedded; (iii) concerns about the meta-schema that the Decision
Tool served to specify and operationalise. I address these three categories of concern
in turn.
As already noted, the Rockwood Frailty Scale is a well-validated clinical tool, being
validated against other established tools,20 through inter-rater reliability,21 and as a
statistically reliable predictor of mortality.22 But as with any tool, it is important to be
clear about the differences between the circumstances under which the tool is validated
and the circumstances under which it is deployed; in the clinical literature this is the
issue known as ‘ecological validity.’23 For example, in one longitudinal study of the tool
as a predictor of mortality, assessors were trained in its application; interviews with the
patient were supplemented by information gathered from family members or other
informants; a final score was assigned only after two separate assessments; and selection
criteria excluded both persons under 65 and anyone unable to provide informed
consent.24 Another survival study excluded patients with “cerebral palsy, severe dementia,
severe hearing disabilities, or the inability to understand English.”25 This is a far cry from
18 See for example: E Harris, Mencap Press Release, 14 April, 2020 <www.mencap.org.uk/press-re-
lease/nhs-decision-making-tool-risks-people-learning-disability-being-refused-life-saving> accessed 26
May 2020.
19 Quoted in ‘NHS ‘Score’ Tool to Decide Who Gets Critical Care’
The Financial Times
(London, 13
April, 2020) <www.ft.com/content/d738b2c6-000a-421b-9dbd-f85e6b333684> accessed 22 May 2020.
20 Rockwood et al (n 14).
21 J. Davies and others, ‘Inter-Rater Reliability of the Retrospectively Assigned Clinical Frailty Score
in a Geriatric Outreach Population’ (2018) 21:1 Canadian Geriatrics Journal 1.
22 NHS Specialised Clinical Frailty Network (n 15).
23 On the concept of ecological validity, see M. Brewer, ‘Research Design and Issues of Validity’ in
H Reis and C Judd, (eds.)
Handbook of Research Methods in Social and Personality Psychology
(Cam-
bridge University Press, 2nd Edition, 2014) 11.
24 Rockwood et al (n 14).
25 J. Lytwyn and others, ‘The Impact of Frailty on Functional Survival in Patients 1 Year after Cardiac
Surgery’ (2017) 154.6 Journal of Thoracic and Cardiovascular Surgery 1990.
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the ‘ecological’ circumstances which prevail at the point of hospital admission during a
pandemic, where triage decisions must be made quickly; access to family members may
be limited; follow-up interviews would come too late to be useful; and the target
population includes persons of all ages and (dis)ability, including many who would lack
capacity to consent to research participation and/or cannot speak English. In light of
these discrepancies, critics expressed doubts about the ecological validity of the frailty
index in pandemic conditions.26Subsequent research has demonstrated that the Frailty
Index is a statistically reliable predictor of mortality in COVID wards,27 but current
guidance nonetheless warns that the instrument is not well-validated for those under
65 and “should not be used in certain groups, including learning disability and cerebral
palsy.”28
The concerns become more acute when we move to the second level, where we consider
the use of the frailty index as one element within the broader COVID-19 Decision
Support Tool. As we have seen, the guiding principle of British triage is to direct scarce
critical resources to the patients for whom they are most likely to make ‘the vital
difference’ – i.e., the difference between living and dying. But does the Decision Support
Tool reliably subserve this function? There is indeed considerable evidence that the
various
components
of the tool are statistically reliable predictors of mortality among
COVID-19 patients: men are indeed less likely than women to survive an ICU COVID-19
ward; older persons are less likely to survive than those who are younger, etc. But we
cannot on that basis conclude that the sum of the four constituent scores (age, gender,
frailty, co-morbidity) is a statistically reliable predictor of mortality in a COVID ICU ward.
At this second level of controversy we find the ingredients for a legal claim of
discrimination. A key underlying problem is that the four variables are not fully
independent. People who are older are more likely to have comorbidities; older people
with co-morbidities are likely to have higher scores on the clinical frailty scale; and so
on. So the underlying risk factors are being doubly or triply counted in the aggregate
score. In logical terms there is a risk of the fallacy of composition here: a property of the
parts (their being reliable predictors of the ‘vital difference’ in COVID ICU) is assumed
to be a property of the whole. In human rights terms, we have the basis for a
discrimination complaint. By being denied access to potentially life-saving treatment
more frequently than others, members of groups defined by a protected characteristic
(age, sex, disability) are treated differently and disadvantageously. Now this in itself is
not sufficient to prove discrimination, since differential and disadvantageous treatment
can in some instances be justified – provided that it relies on reasonable and objective
criteria of differentiation to fulfil a legitimate purpose.29 In this instance the purpose is
clear: saving as many lives as possible. As we shall see presently, even this noble aim
26 S Moug and others, ‘Decision-Making in COVID-19 and Frailty’ (2020) 5 Geriatrics 30.
27 Hewitt and others, ‘The Effect of Frailty on Survival in Patients with COVID-19 (COPE): a Multi-
centre, European, Observational Cohort Study’ (2020) 5 Lancet Public Health e444.
28 A Bloomer, ‘COVID-19: NICE Clarifies Use of Frailty Score in New Rapid Guidance,’ (2020) GM
Journal 24 March, 2020 <www.gmjournal.co.uk/covid-19-nice-clarifies-use-of-frailty-score-in-new-rapid-
guidance> accessed 26 November 2020.
29 For this particular formulation of the defence against an allegation of discrimination, see UN
Human Rights Committee,
General Comment 18: Non-Discrimination
(1989), para. 13. In UK law, the rele-
vant provision of law refers to a “proportionate means of achieving a legitimate aim.”
Equality Act
(2010),
sec. 13(2) and 19(2).
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raises some thorny human rights concerns. But the immediate problem at this second
level of controversy concerns not the aim but the means of pursuing it. The standing of
the COVID-19 Decision Support Tool as a reasonable criterion for differentiation depends
on its ecological validity as a predictor of who will (and will not!) benefit from treatment.
But the double-counting problem renders this validity doubtful.
The aforementioned problems pale in comparison to the third level of controversy: the
meta-schema of the British triage system itself. As we have seen, the ethical intuition
underlying the meta-schema seems all but irresistible: in triage conditions, use scarce
resources so as to save as many lives as possible. This much might seem obvious.
Wouldn’t any other use of such resources be a dereliction of duty? If the meta-schema
is accepted, then the problems we have canvassed so far are at most flaws of
implementation. The Decision Support Tool does not survive scrutiny if it is not properly
calibrated to fulfil the imperative of ‘British’ triage. It therefore seems to fail the
‘reasonable means’ test. The remedy would be to refine or replace it with a more carefully
calibrated tool, supplemented by clinical judgement. Before striking off down that path,
however, we need to consider whether that is the right direction-of-travel, when assessed
from a human rights point of view.
To see the concern at this third level, we have to come to terms with two simple truths
which, taken together, have troubling consequences. The first truth is that the patients
who are most likely to survive in a COVID ICU unit are those who had the best pre-
morbid health and fitness. The second truth is that various vulnerable populations in
our society have, on average, lower health and fitness. The troubling consequence:
members of vulnerable populations who are
already
disadvantaged will be
further
disadvantaged by policies which implement the British meta-schema in the context of
the pandemic. Alas this ‘doubly disadvantaged’ group includes both the elderly and
persons living with disabilities. These concerns were aptly summed up in a forceful
public statement from the CEO of one disability advocacy group:
[T]his latest Decision Making Tool… presents a double whammy for people
with a learning disability, penalising them for needing extra support with
everyday activities, as well as for having a neurological condition. Are we
reduced to refusing healthy people life-saving treatment because they have
a disability? I sincerely hope not.30
Despite all these concerns, there is one sense in which the fate of the COVID-19 Decision
Support Tool can be viewed as a human rights success story. Frontline practitioners
confronted an enormously challenging care-situation which directly threatened the
human rights of those affected by it. In response, they designed a principled approach
to the problem, and they undertook to be explicit about the basis for the hard choices
that were looming. They then shared their tool publicly, facilitating public scrutiny. The
critical discussion that ensued in the media and in civil society was informed by human
rights standards, particularly with regard to discrimination, and exposed serious human
rights concerns. But as the flaws became apparent, the relevant public body quickly and
explicitly distanced itself from the tool and made clear that its use was not authorised
30 E Harris (n 18).
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in the service. All this can be seen as an example of the human rights framework
influencing policy and practice in real time, without reliance on the cumbersome
mechanisms of judicial review.
4. Alternatives to the Meta-Schema
The failure of the COVID-19 Decision Support Tool seems to leave us back with our
original problem. How
should
the health services respond to a situation in which
demand for live-saving interventions massively swamps supply? And more specifically:
how should policy be designed so as to ensure respect for human rights in such
situations? In returning to these questions in light of what we have learned, it will be
worth recalling the UN joint statement that we considered at the outset. As we have
seen, the‘No Exceptions’ headline from that statement proved to be ill-suited as a guide
to policy formation in a triage situation. But recall how that headline message was
elaborated in the body of that statement: “The scarcity of resources… should never be a
justification
to discriminate
against certain groups of patients.”31 This elaboration gives
a more definite shape to the challenge. Once demand swamps supply, the imperative
can no longer intelligibly be to ensure that no one is denied access to live-saving
interventions. But we can seek to
avoid discrimination
in making the hard decisions
that ensue.
As we have seen, however, avoiding discrimination in triage is by no means
straightforward. I have already summarised the case for concluding that the COVID-19
Decision Support Tool is itself discriminatory. The meta-schema of British triage may or
may not itself be discriminatory, but its differential impact on already disadvantaged
groups raises concerns that are sufficiently serious from a non-discrimination point of
view that alternatives must be considered.32 By way of conclusion I survey four
alternatives to the meta-schema. It is not my purpose here to advocate for any one of
these alternatives, but it will be worthwhile identifying some of their respective
attractions and problems before offering a few final observations.
4.1 Alternative 1: First-Come-First-Served
One simple response to a triage situation would be to allocate available resources to
those who present first. Defences of this approach can be found,
inter alia
, in debates
within the rabbinical tradition over moral dilemmas created by scarcity.33 In theological
terms, this approach avoids putting doctors in a position where they are ‘playing God’
31 ibid (n 7) (emphasis added).
32 On most legal approaches to discrimination, a practice does not amount to discrimination if it is
in the service of a legitimate aim and uses a reasonable means for pursuing that aim. As we saw above,
the COVID-19 Decision Support Tool fails the
reasonable means
test. But a better calibrated implementa-
tion of the underlying meta-schema might well pass that test. If so, then use of the meta-schema would
not be discriminatory under the usual ‘pragmatic definition’ of discrimination. For a recent discussion of
the pragmatic definition of discrimination and alternates thereto, see S Gurbai, ‘Beyond the Pragmatic
Definition? The Right to Non-Discrimination of Persons with Disabilities in the Context of Coercive Inter-
ventions’ (2020) 22 Health and Human Rights (early online) <www.hhrjournal.org/2020/05/beyond-the-
pragmatic-definition-the-right-to-nondiscrimination-of-persons-with-disabilities-in-the-context-of-coerciv
e-interventions> accessed 26 November 2020.
33 For a recent discussion, see: A Solnica, L Barski and A. Jotkowitz, ‘Allocation of Scarce Resources
during the COVID-19 Pandemic: A Jewish Ethical Perspective’ (2020) 46 Journal of Medical Ethics 444.
33
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in deciding who lives and who dies. In secular terms, it has the advantage of concordance
with one important understanding of the basic ethos of medicine:
Aid those who stand
before me.
This first alternative was recently endorsed by a German district court judge
(Judge Nancy Poser, who is herself living with a serious disability) in an interview with
a German journalist. “
Aus ihrer Sicht wäre nur ein Prinzip gerecht: Wer zuerst da ist,
bekommt auch die Behandlung
.” [“From her point of view, only one principle would be
fair: whoever is there first gets the treatment.”]34But does this approach successfully
avoid discrimination? It is far from clear that it does. One problem is that some of the
same populations who are disadvantaged under the meta-schema of British triage will
also be those who have the least ability to present themselves in a timely fashion for ICU
admission. If so, then they might once again find themselves lower down in the queue
that determines eligibility for treatment – precisely by virtue of their membership of one
of the groups protected under anti-discrimination legislation!
4.2 Alternative 2: Lottery/Randomisation
A second alternative would be to resort to randomisation when demand exceeds supply.
This approach has some of the same advantages as Alternative 1 insofar as it takes
clinicians out of the role of ‘playing God.’ In theological terms, a lottery ‘leaves the matter
to God’; in secular terms, it is ‘left to chance.’ A further advantage of this approach is that
it gives expression, in concrete policy terms, to the idea that every life is of equal worth.
However it is important to consider how such a policy would play out in practice, and
what impact it might have on those who implement it. As a lived reality, a randomisation
procedure would produce situations where an ICU team is instructed by some machine-
generated ranking to spend time, energy and resources on one patient while leaving
others waiting. If those clinicians can see that their efforts are unlikely to help the first
patient but might well save the second (or the second and third…), then the costs in moral
distress for the clinicians could be significant.35 Since moral distress is known to be
associated with workforce dropout in critical care services,36 this could in turn have
significant knock-on effects for the health service and hence for the general public. It is
perhaps significant to note that a Change.org petition advocating for randomisation at
the height of the first wave of the pandemic attracted only about 1,000 signatures.37
4.3 Alternative 3: Dilution
This third alternative comes closest to capturing ‘the official story’ of what happened
in the UK during the first wave of the COVID-19 pandemic. The strategy, to put the
point somewhat paradoxically, is to respond to a triage situation by
avoiding triage
.
To understand this approach, we need to return to the two graphs that we considered
34 L. Gather, ‘Klage gegen Triage: ‘Dann werde ich abgehängt,’’
Tagesschau
17 Nov., 2020;
<www.tagesschau.de/inland/verfassungsklage-triage-101.html> accessed 25 November 2020.
35 On the concept of moral distress, see D Batho,
What Is Moral Distress? Experiences and Re-
sponses
, (University of Essex: EOP Green Papers, 2018);
<https://powerlessness.essex.ac.uk/moral_distress_green_paper> accessed 26 Novembre 2020.
36 B Whittaker, D Gillum and J Kelly, ‘Burnout, Moral Distress and Job Turnover in Critical Care
Nurses’ (2018) 3.3 International Journal of Studies in Nursing 108.
37 M Holmes and J Adams, ‘Only a Lottery will Avoid Ventilator Rationing by Privilege’
<www.change.org/p/jerome-adams-md-only-a-lottery-will-avoid-ventilator-rationing-by-privilege-
6fab9b08-1419-4652-85b8-1ebc9e21a004> accessed 24 November 2020.
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at the outset. (See Figs. 1 and 2.) Recall that both graphs included a line that
represented ‘surge capacity.’ Recall also that in each of the two graphs, surge capacity
was represented as a horizontal line – that is, as a constant over time. But of course
actual capacity
increased dramatically through a variety of mechanisms:
redeployment of staff, deferral of non-critical services, the opening of so-called
Nightingale Hospitals, and so on. The aim was to ensure that no one was denied
treatment. As we have seen from the Amnesty report quoted at the outset, this aim
was not achieved for all – self-congratulatory press statements from Boris Johnson
notwithstanding.38 But pursuit of that aim also came at a cost: the quantity of ICU
care was massively increased, but the quality was diluted.
This compromise was powerfully captured by one experienced frontline clinician in NHS
Wales, speaking at a webinar held at the end of April:
In the UK we have
not
moved to a position where critical care is resource-
limited. So we have
not
moved to a position where we are having to triage
patients on the grounds of limitation of the available resource. But we have
only been able to do that by what is called ‘surge capacity,’ so there has
been a massive increase in the amount of critical care that we can deliver
– up to about four times the usual number of critical care beds. But the only
way to do that is to dilute the critical care resource. We are sharing it out
over a large number of patients, but with the same number of intensive
care nurses. ... The problem with diluting care is that it does come then
with risks. We have had to dilute the standards, and when you dilute the
standards, the outcomes get worse.39
The opening claim from this frontline report will certainly not ring true to those like the
family in Cumbria, who experienced all too palpably the restrictions on access to critical
care-resources. But the great advantage of this approach, where it succeeds, is that
everyone gets some care, even if the quality of that care is diminished. Moreover, such a
plan is powerfully expressive of another ideal that is often expressed (if also
unsympathetically received40), viz., that
we are all in this together
. But we also have to
recognise that the strategy has built-in limits. At some point along the trajectory of
dilution, critical care becomes ICUNO –
ICU in Name Only
. And of course if a system
finds itself at the terrible crossroads where demand swamps
even surge capacity
, then
some method of prioritising must be adopted. As a general solution to the problem of
human-rights-compliant-triage, dilution cannot stand alone.
38 On 30 April, 2020, Boris Johnson gave a press statement in which he reported: “[A]t no stage
has our NHS been overwhelmed. No patient went without a ventilator. No patient was deprived of inten-
sive care.” <www.conservatives.com/news/prime-minister-tackling-coronavirus> accessed 30 November
2020. We now know that this claim is not true.
39 Jack Parry Jones, Oral Statement to the National Mental Capacity Forum (28 April 2020); record-
ing available at <https://autonomy.essex.ac.uk/covid-19> accessed 8 December 2020 (Webinar #2; time-
stamp: 54:50).
40 A. Orr, ‘Letter to the Editor: We are not all in this together when it comes to Coronavirus’
The Independent
, (London, 15 April 2020) <www.independent.co.uk/voices/letters/coronavirus-
lockdown-germany-nhs-scotland-a9465991.html> accessed 25 November 2020.
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4.4 Alternative 4: And the Last Shall Be First
I conclude this (non-exhaustive) list with an alternative that was suggested by Amita
Dhanda at the Validity Webinar where an earlier version of these remarks was presented.
Without presuming to speak for Dhanda, or to put words in her mouth, I understood
her suggestion to be that priority should be given to those whose antecedent background
situation left them most disadvantaged. Early on in the COVID-19 pandemic, it became
clear that the burden of the illness was falling most heavily on certain populations who
were already in disadvantaged positions in society. As we have seen, the standard
approach of ‘British’ triage exacerbates that problem, insofar as those very same
populations tend to have lower pre-morbid health and fitness and hence, under the
British meta-schema, are less likely to receive critical care. Dhanda’s proposal would
respond to this situation by putting those antecedently disadvantaged populations at the
front of the queue in triage situations, even if this means leaving some among the already
privileged portion of the population to ‘fend for themselves.’41
5. Five Lessons from the UK
What lessons should we learn from all this? First and foremost, we have to
acknowledge the profound difficulty of ensuring respect for human rights in the
particularly challenging circumstances created by pandemic triage situations. It is all
well and good to insist that “everyone has a right to health,” but it is something else
entirely to ensure respect for that right when there is not enough supply of critical
resource to go around.
Second, it is important to recognise that responses to triage situations have an ethical
substructure. In one respect this may of course seem obvious: the decisions and policies
we have been considering are literally matters of life and death; what could be more ethically
significant than that? But in the task of developing triage responses, this ethical
substructure can sometimes slip from view. Triage policy comes to sound like a task of
logistics, maximisation and consequentialist calculation: how can we achieve the maximum
benefit and the minimum harm with the limited resources available? (I have heard more
than one clinician describe triage as ‘a math problem.’) But triage situations
become
calculable
only insofar as we are already operating within a framework that
renders them
calculable
. The meta-schema of the British triage system is one such framework.
The last
shall be first
is another. The important point is that these meta-schemas themselves carry
ethically substantive commitments. They both reflect and articulate ethical
ideals
that are
then
real-ised
(literally:
made real
) in concrete policy and practice.42
41 Dhanda’s proposal resonates with one of the historical alternatives to the British approach to
triage. One of the earliest systematic approaches to triage was developed by Dominique Jean Larrey, who
was the surgeon general in Napoleon’s revolutionary army. Larrey, who is often credited as ‘the inventor
of triage,’ was an extraordinary innovator in military medicine, and developed a novel approach to the
treatment of battlefield casualties. Larrey’s approach reflected some of the ideals of revolutionary France.
Priority for aid should be given to those who are “most dangerously wounded, … without regard to rank
or distinction.” Moreover, medics should assign a
lower
priority to officers, “who generally have the
means of transportation” (i.e., horses) and so are left to fend for themselves. DJ Larrey,
Mémoires de
chirurgie militaire et Campagnes
(Smith, 1812), 3:4. Translation by R Hall,
Memoirs of Military Surgery, and
Campaigns of the French Armies
(J Cushing; 1814), 2:123.
42 For a recent exercise using deliberative democracy to choose among resource allocation strate-
gies during the pandemic and to identify the values at work therein, see P Carroll, C Juliette and T Cooper,
‘Resource Allocation, Age and COVID-19’ (
Ipsos MORI,
2020) <www.kcl.ac.uk/policy-
institute/assets/resource-allocation-age-covid.pdf> accessed 26 Nov., 2020.
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Thirdly, when engaging with that ethical substructure, we need to be alive to the
possibility that seemingly obvious ethical intuitions (“save the most lives possible”) may
have unforeseen or unintended consequences when used to guide policy in the extreme
conditions of pandemic triage. Some of these consequences raise significant human
rights concerns.
Fourth: among those human rights concerns, one issue that looms particularly large is
discrimination; I have here been particularly concerned with discrimination on the basis
of age or disability. The legal and policy issues here are complex, and the solution is far
from obvious. But as we have seen, some well-intentioned responses to the triage
challenge fall foul of non-discrimination obligations, and the traditional British triage
system itself has consequences that are sufficiently troubling that alternatives must be
considered.
Finally, one important lesson that we have learned from the British experience is that
robust civil society discourse and debate, guided by sensitivity to human rights norms,
can be a significant force in refining policy in real time, even under the extraordinary
pressures of a global pandemic. That is certainly a welcome finding, as much remains to
be done.
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