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The eugenic roots of ‘quality adjusted life years,’ and why they matter

Why a powerful House Republican wants to ban a common insurance practice

House Energy Committee Chairwoman Rep. Cathy McMorris Rodgers (R-Wash.) speaks during a subcommittee hearing about the federal response to the coronavirus pandemic on Feb. 8. (Drew Angerer/Getty Images)
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Last month House Energy and Commerce Committee Chairwoman Cathy McMorris Rodgers (R-Wash.) introduced H.R. 485, the Protecting Health Care for All Patients Act, which would prohibit the use of “QALY” — quality adjusted life years — in all federal health insurance programs. The metric has become increasingly appealing to health insurance providers in the United States as a way to reduce spending in the face of soaring health-care costs. Yet, McMorris Rodgers charges that the measurement is used to “discriminate against people with chronic illnesses and disabilities … putting them at the back of the line for treatment.”

She is right. While QALY plays a significant role in health-care decisions in the United States, it puts people with disabilities like Down syndrome, ALS and cystic fibrosis at a medical and economic disadvantage.

Here’s how it works: QALY is a formula used to predict how much a particular treatment or drug prescription will extend the life of a patient and increase the quality of life experienced during those years. To make this prediction, it lowers the value of treatment by the degree to which an illness or disability is perceived to harm a person’s quality of life, which is assessed on a scale between zero and one — with one representing perfect health and zero representing death. Ari Ne’eman, a disability rights advocate, has explained, “If we were to assign autism a disability weight of 0.2, that would mean that a year in the life of an autistic person would be worth 80 percent of a nondisabled person’s life.”

In this way, QALY prioritizes treatments that have more potential to return able-bodied patients to perfect health and provides less support for treatments that might extend the life of someone who has a disability or incurable chronic condition. QALY is derived from population outcomes and is not intended for use in decision-making for individual patients. Nonetheless, the metric recalculates the lives of people with disabilities and finds them inadequate in the face of mathematical abstractions like “normal” and “perfect health.”

Although QALY is a relatively new measurement, the recalculation of the age of people with disabilities has been a common practice in medicine and psychology dating back to the 19th century. Those classified as “feebleminded” or “backward” were often described as halted in an early stage of childhood. Physicians working in state institutions and asylums referred to their patients of whatever age as happy, naive children. These labels reflected how medical and psychiatric care at that time performed a custodial role. Physicians believed that people with intellectual differences were too childlike to make medical decisions for themselves and considered them morally pernicious and a threat to the well-being of society.

During the 20th century, efforts to care for people with disabilities by trying to measure how much they deviated from normal increased. The French psychologist Alfred Binet first developed a scientific way of expressing intelligence through age in 1905. Binet’s test consisted of short tasks that related to basic expectations for comprehension and reasoning. Children were asked to label parts of the body, to describe the difference between a fly and a butterfly and to use scissors to cut a specified shape out of a piece of paper. Binet sequenced the assigned tasks according to their difficulty. A child proceeded through the exam until they could no longer complete the tasks. The age associated with the last task they could perform was their assigned mental level. This number was divided by the child’s chronological age to arrive at their intelligence quotient, or IQ.

The purpose of Binet’s IQ test was to identify children in the French public school system who might benefit from extra help in the classroom. But the American psychologist Henry Goddard wondered if Binet’s test might be used to identify a child’s entrenched and inherent intellectual capacity. Goddard solidified the idea of mental age, which provided a radical reframing of time. Mental age prioritized a linear sense of intellectual growth and progress measured in relation to someone’s actual age. In a “normal” child, those two ages were in sync. But in “feebleminded” children, mental age lagged behind.

Using Binet’s tests, Goddard proposed the use of distinct terms to identify those who did not progress normally. He decided “idiot was the best term to describe those who had no higher intelligence than a 2-year-old. Those who had the intelligence expected of a child between 3 and 7 years old would be “imbeciles.” For a third grouping, those with a mental age from 8 to 12, Goddard proposed a new term: “moron.”

Goddard claimed that the calculation of mental age was scientifically legitimate, yet the desire to devalue the lives of those with disabilities remained. “The conclusion is forced upon us that it is very unfair to the normal child to keep these children in the same class with him,” he wrote in 1911. Goddard argued that those who performed poorly on an IQ test were not worth the financial investment and efforts of public education.

Goddard’s work with Binet’s IQ test married statistics to discrimination, providing a scientific logic that supported eugenic sterilization. “Three generations of imbeciles are enough,” Supreme Court Justice Oliver Wendall Holmes Jr. declared in 1927 in his majority opinion in Buck v. Bell, which ruled that the forced sterilization of those with low IQs did not violate the 14th Amendment’s Equal Protection Clause.

While the eugenics movement is the most extreme and horrific example of how people with disabilities have been deemed less valuable based on idealized conceptions of health, the basic logic behind this thinking has persisted. Encouraged by the accuracy of methods used in the U.S. Department of Defense, the Department of Health, Education, and Welfare produced a report in 1966 recommending that cost-benefit analysis be used by third-party payers and health agencies of all kinds. “In the not too distant future … it will be possible to rank diseases and health problems according to the economic burden they place on our communities, and to select and develop our programs along lines which will assure the greatest return for our investment in health services.”

A number of formulas for cost-benefit analysis in health care emerged, including those with brutal names such as “time trade-off,” “standard gamble” and “person trade-off.” All of these eventually informed the development of the phrase “quality adjusted life year,” which was first used by a group of researchers at the University of California at San Diego in 1972.

As a particular form of cost-benefit analysis, QALY began to gain popularity in the 1980s. However, in 1992 the George H.W. Bush administration found that one of the boldest attempts to utilize QALY in a state-run health insurance program violated the Americans With Disabilities Act. Starting in 1989, Oregon had attempted to reform its Medicaid program by ranking treatments in terms of their cost-effectiveness. Oregon ranked these treatments according to certain criteria, including quality of life and life expectancy determined by QALY. In a letter to the editor in the New York Times, a Bush administration official stated that “Oregon’s plan in substantial part values the life of a person with a disability less than the life of a person without a disability.”

Despite this setback, the use of QALY in federal programs has steadily increased in the last 10 years due to concerns about rising health-care costs.

Perhaps QALY wouldn’t seem acceptable if we weren’t already so used to calculated predictions that maximize functioning and performance outcomes but minimize the value of the lives of people with disabilities. But this calculation is not inevitable. Several alternatives to QALY have been proposed that acknowledge the complexity of health-care decisions and calculate the cost of medical treatment without penalizing disability. The best alternative would require us to accept disability as a valuable part of the diversity of human life, rather than a strange distortion in time.