by Joseph Stramondo, Ph.D.
While I have warned against using quality of life criteria when developing triage protocol, what about the strategy of using as a criterion the likelihood of whether a patient will survive COVID-19 even with aggressive treatment? On the face of it, this seems safer from ableist bias than the previously examined quality of life criterion. After all, even Ne’eman – who defends the view that the best way to avoid ableist bias is for people to be cared for on a first come first served basis, regardless of other factors – admits that patients should not be provided with futile care that will not actually save their life from the virus. Of course, judging the futility of a treatment is a rather inexact science under the best of circumstances. In the context of pandemic triage, what we are really talking about is not futility, but a scale of likelihood of survival. That is, there will not be a clearly discernable bright line between those for whom treatment is absolutely futile and those who are merely unlikely to survive. Further, there will be significant overlap between the population of patients that are unlikely to survive even with treatment and those that have disabilities, some of which will entail comorbid risk factors. However, this isn’t itself an argument that such a likelihood of survival criterion is intrinsically and unfairly biased in the same way that quality of life considerations seem to have ableist bias baked right in.
If and when tragic choices need to be made, it seems that some disabilities are relevant in as far as they are associated with comorbidities that we are reasonably sure will reduce the likelihood a patient will respond to treatment and survival. There is still a risk that ableist bias finds its way into the application of this sort of likelihood of survival criterion, but there are ways to reduce this risk. A deeper concern is whether we ought to also deprioritize, on the same grounds, disabled folks that may have as good a likelihood of surviving as anyone else, but require more treatment to get there. We can call this the level of resource commitment criterion. Ultimately, can we consistently justify excluding patients that are less likely to survive in order to conserve resources (and thus save more lives) without also excluding patients who will use more than an average amount of resources to survive? I think we can.
Given that there is still so much to learn about COVID-19, there are going to be as many questions as certainties when making judgments about how various comorbidities effect prognosis. Some data will be available from other parts of the world that were hit earlier by the disease, but with such a condensed time frame, these data seem likely to have significant limits. This is made even more complicated by the enormous variation between patients. Consider, the case highlighted in the press release announcing the recent legal action against the state of Washington, “I am concerned that a doctor will see my diagnosis of cystic fibrosis in my chart and make lots of erroneous assumptions about me. Cystic fibrosis often comes with significant breathing difficulties and a life expectancy of 30 years . . . However, tests show that I have better breathing capacity than most people without cystic fibrosis . . .” I think the worry being expressed here is that, in its application, the likelihood of survival criterion will sometimes slip into ableist bias by relying on disability as a heuristic. As Jackie Leach Scully puts it in her discussion of using likelihood of survival as a triage criterion, since disabled people are stereotypically assumed to be ill, “individual differences mean global rules (of the “no one with cystic fibrosis to be placed on ventilation” kind) could easily be unjust.” So, even if, in general, people with disability X that typically occurs with comorbidity Y are less likely to survive, we ought to do our best to ensure that actual person P with disability X truly has comorbidity Y before denying treatment. Otherwise, there is a good chance that the denial is being motivated by stereotype rather than evidence. This is the sort of scenario the HHS Office of Civil Right’s recent bulletin is trying to account for when it states, “. . . whether an individual is a candidate for treatment should be based on an individualized assessment of the patient based on the best available objective medical evidence.”
Feminist bioethicist Alison Reiheld has argued that some kind of feedback loop would be the best way to account for these biases. One procedural safeguard would be for hospitals to conduct reviews of triage decisions against treating someone who would have been a candidate for treatment under ordinary circumstances. This is not to say that such decisions are inherently discriminatory. After all, these are not ordinary circumstances. However, this could be a trigger for closer examination of a case and watching for ableist bias in the misapplication of the likelihood of survival criterion may cut down on errors in which a person is unfairly assumed, contrary to evidence, to be less likely to survive because of a disability.
The motivation behind denying resources to those that are less likely to survive is that those resources can then be used to save others who are more likely to survive. It is an attempt to maximize the number of lives saved. If we endorse this kind of thinking, are we then committed to also withholding resources from those who have a good chance of survival, but only by using more resources? After all, this too would increase the number of people who survive. I think we can actually accept the likelihood of survival criterion while rejecting the level of resource commitment criterion, even if both aim at maximizing the number of lives saved.
According to the first criterion, patients that fall below a threshold of likelihood that they will survive may be turned away because these scarce resources may be wasted. This is the scenario in which the ICU bed is filled, the ventilator is in use, and yet the patient dies. With the second criterion, it may take more resources to get the job done, but those resources aren’t wasted, they save someone’s life. This may be inefficient, but is surely not wasteful. Inefficiency implies that a resource was not used to achieve its maximum benefit. Waste implies that a resource was not used to achieve any benefit.
It would be a serious moral error to equate these two scenarios. Harking back all the way to the American eugenics movement, there is a long, grim history of confusing inefficiency with wastefulness when it comes to the fair treatment of disabled people. One could even conceptualize the entire disability rights movement as an attempt to draw this distinction. It may reduce efficiency to bring disabled people into the mainstream of education, employment, and so on, but that does not mean that the resources used to do this are wasted.
I see no reason why we can’t draw this same distinction when it comes to triage. By ignoring the level of resource commitment criterion, it is true that fewer lives will be saved, but perhaps it would guarantee greater fairness when it comes to individuals’ chances to access care that they would benefit from. This sort of fairness would not be a waste.