[2007.3.15]Evidence-based ethics: Logical endings

Evidence-based ethics

Logical endings

Mar 15th 2007
From The Economist print edition

Computers may soon be better than kin at predicting the wishes of the dying

IN 1947 a psychologist called Theodore Sarbin made a controversial suggestion to a medical conference. He proposed that a doctor is really just a machine whose purpose is to make actuarial judgments about the best treatment for a patient. And not a very good machine, at that, for Sarbin also suggested that medicine would benefit if “we could replace [the doctor’s] eyes and brain with a Hollerith machine”.
在1947年的一次医学大会上,心理学家西奥多•沙宾(Theodore Sarbin)的意见引起了争论。他提出,医生不过是一台机器,其目的是为了对患者获得最优治疗方案作出保险精算的判断,而且还不是一台很好的机器。沙宾指出,如果“我们能够用一台霍勒里斯机器换掉(医生的)眼睛和大脑”,医学才会让人获益。

It was a remarkably prescient vision. The idea that Hollerith machines (or computers, to give their modern name) might sometimes be better than doctors at deciding how to treat a patient is now universally accepted. A computer program is, for instance, sometimes used to recommend whether the horrors of chemotherapy are likely to outweigh its blessings.

When machines trespass into the area of medical ethics, though, hackles rise. Here it is not the doctor that is being second-guessed, but the patient’s relatives. The question is, if you were in a coma, whom would you more trust to come to the conclusion that you would want: your spouse or a machine?

David Wendler, of the National Institutes of Health in Bethesda, Maryland, and his colleagues have looked into this question. Their answer, just published in the Public Library of Science Medicine, is surprising. At the moment, both are equally reliable—but only the machines are likely to get better at it.
马里兰州贝塞斯达美国国家健康研究所的大卫•温德勒(David Wendler)和他的同事对这一问题进行了调查。刚刚发表在《科学医学公共图书馆》杂志上的调查结果出乎人的意料:在那种情况下,两者的可信赖程度相同,但机器所作的结果有可能更为可靠。

Dr Wendler’s study began last year, when his team reviewed all the experiments they could find that had attempted to test how well people predict the wishes of patients with life-threatening conditions. Some of these studies used real patients whose conditions might have led them to fall into a coma—when, obviously, they could not make the decision for themselves. Others employed surrogates who were asked to make “living wills” outlining their preferences for treatment (or the lack of it) in various hypothetical circumstances. The desires expressed by these patients, whether real or surrogate, were then compared with what those patients’ kin predicted the patients would want, and also with the predictions of unrelated people (doctors, for example) who might be called on to make the decision if kin could not be found.

Dr Wendler found 16 published reports containing almost 20,000 pairs of decisions. His analysis showed that kin and patient agreed only 68% of the time. When they did not agree, kin were more likely to recommend treatment when the patient wanted treatment withdrawn rather than mistakenly to recommend withdrawal. Surprisingly, the bias towards treatment was equally strong when the decision was made by an unrelated person such as a doctor.

Other research has suggested that the variable most reliably governing whether a patient would want the machine turned off is the “1% rule”. This is that people seem to want life-saving interventions if there is at least a 1% chance they will recover the ability to reason, remember and communicate. Less than 1%, and it is time to pull the plug.
其他研究已经表明,决定一个患者是否希望中止抢救的最可靠变量是“1% 规则”。也就是说,如果至少有1%的可能性恢复思考、记忆和交流能力,那么人似乎就希望采取挽救生命的措施。如低于1%,就可以拔掉插管(放弃)了。

Calculating will

Using that rule of thumb, Dr Wendler and his colleagues wrote a computer program that assesses the prognosis for a patient, based on the sort of clinical criteria that the studies had described to both patients and predictors. Only 12 of the 16 original studies contained sufficient detail to be used, but the result was remarkable. In these 12 studies, human predictors guessed the patient’s wishes rather more accurately than was true when all 16 were lumped together—getting them right 78.4% of the time. Dr Wendler’s program achieved an almost identical result—78.5%.

Since that result is based on a single criterion, the 1% rule, Dr Wendler reckons he can beat it by adding other factors to the program. Older patients may be less willing to accept heroic, invasive surgery than younger ones; men might think differently from women; professors imagining themselves with advanced dementia may more readily turn down pneumonia treatments than dancers would. Dr Wendler’s guess is that by studying such preferences in more detail and adding them to the program, he might increase its accuracy by as much as another ten percentage points.

At the moment, such data do not exist. No one has yet had a reason to collect them. But they do have a reason now. The decision about when to pull the plug on a patient who is not expected to recover is unlikely ever to be handed over completely to a machine. But when no kin can be found, the program’s opinion might help. And even when a dying patient is surrounded by people who care about him, those people may welcome some guidance about what his wishes were likely to have been. Individuals are, indeed, individual. But that does not mean their dying wishes are all that different.

霍勒里思,赫尔曼:(1860-1929) 美国发明家,他发明了能够在穿孔卡片上贮存和再现信息的系统(1880年)并创建了后来发展为IBM的公司(1924年)


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