Quality-Adjusted 

Life Years and the 

Devaluation of Life 

with Disability

Part of the Bioethics and 

Disability Series

National Council on Disability

November 6, 2019
National Council on Disability (NCD)

1331 F Street NW, Suite 850

Washington, DC 20004

Quality-Adjusted Life Years and the Devaluation of Life with Disability: Part of the Bioethics and 

Disability Series

National Council on Disability, November 6, 2019

This report is also available in alternative formats. Please visit the National Council on Disability (NCD) 

website (www.ncd.gov) or contact NCD to request an alternative format using the following information:

ncd@ncd.gov Email

202-272-2004 Voice

202-272-2022 Fax

The views contained in this report do not necessarily represent those of the Administration, as this and 

all NCD documents are not subject to the A-19 Executive Branch review process.
National Council on Disability

An independent federal agency making recommendations to the President and Congress 

to enhance the quality of life for all Americans with disabilities and their families.

Letter of Transmittal

November 6, 2019

The President

The White House

Washington, DC 20500

Dear Mr. President:

On behalf of the National Council on Disability (NCD), I am pleased to submit Quality-Adjusted Life 

Years and the Devaluation of Life with Disability, part of a five-report series on the intersection of 

disability and bioethics. This report, and the others in the series, focuses on how the historical and 

continued devaluation of the lives of people with disabilities by the medical community, legislators, 

researchers, and even health economists, perpetuates unequal access to medical care, including lifesaving care.

When health insurance will not cover medically necessary medications and treatments, individuals 

experience poorer health and a lower life expectancy. Nonetheless, in an effort to lower their healthcare 

costs, public and private health insurance providers have utilized the Quality Adjusted Life Year (QALY) 

to determine the cost-effectiveness of medications and treatment. QALYs place a lower value on 

treatments which extend the lives of people with chronic illnesses and disabilities. In this report, NCD 

found sufficient evidence of the discriminatory effects of QALYs to warrant concern, including concerns 

raised by bioethicists, patient rights groups, and disability rights advocates about the limited access to 

lifesaving medications for chronic illnesses in countries where QALYs are frequently used. In addition, 

QALY-based programs have been found to violate the Americans with Disabilities Act.

The US government does not have a single comprehensive policy on QALYs. Some federal agencies 

are banned from utilizing measurement tools like QALYs, while some state and federal partnership 

programs, such as state Medicaid programs, may. NCD is troubled that health insurance providers, 

government agencies, and health economists are showing increasing interest in using QALYs to 

contain healthcare costs despite QALYs’ discriminatory effect.

The lives of people with disabilities are equally valuable to those without disabilities, and healthcare 

decisions based on devaluing the lives of people with disabilities are discriminatory. Quality-Adjusted 

Life Years and the Devaluation of Life with Disability explains QALYs and their effect on the availability 

of medical care for people with disabilities and chronic illnesses. It makes recommendations to 

Congress, federal agencies, and public and private insurers directed at rejecting QALYs as a method of 

measuring cost-effectiveness for medical care and offers alternatives.

1331 F Street, NW ■ Suite 850 ■ Washington, DC 20004

202-272-2004 Voice ■ 202-272-2074 TTY ■ 202-272-2022 Fax ■ www.ncd.gov
NCD stands ready to assist the Administration, Congress, and federal agencies to ensure that people 

with disabilities and chronic illnesses have access to the medical care they need.

Respectfully,

Neil Romano

Chairman

(The same letter of transmittal was sent to the President Pro Tempore of the U.S. Senate and the Speaker of the 

U.S. House of Representatives.)

2 National Council on Disability
National Council on Disability Members and Staff

Members

Neil Romano, Chairman

Benro Ogunyipe, Vice Chairperson

Billy Altom

Rabia Belt

James Brett

Daniel Gade

Andrés Gallegos

Wendy S. Harbour

Clyde Terry

Staff

Phoebe Ball, Legislative Affairs Specialist

Stacey S. Brown, Staff Assistant

Joan M. Durocher, General Counsel & Director of Policy

Lisa Grubb, Executive Director

Netterie Lewis, Administrative Support Specialist

Amy Nicholas, Attorney Advisor

Nicholas Sabula, Public Affairs Specialist

Amged Soliman, Attorney Advisor

Anne Sommers, Director of Legislative Affairs & Outreach

Ana Torres-Davis, Attorney Advisor

Keith Woods, Financial Management Analyst

Quality-Adjusted Life Years and the Devaluation of Life with Disability 3
4 National Council on Disability
Contents

Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  

Executive Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1

Key Findings . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1

Key Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Congress . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

US Department of Health and Human Services (HHS), 

Office for Civil Rights (OCR); US Department of Justice 

(DOJ) Civil Rights Division . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

HHS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1

HHS, OCR . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1

HHS, CMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1

Acronym Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  1

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Summary of Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2

Qualitative Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2

Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2

Chapter 1: How QALYs Are Calculated and the Impact on People with 

Disabilities and Patients with Chronic and/or Degenerative Illnesses . . . . . . . . . . . .  2

The Purpose of QALYs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2

What QALYs Represent . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2

Why QALYs Are Used . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2

Cost-Effectiveness Studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2

Calculation of Quality-Adjusted Life Years . . . . . . . . . . . . . . . . . . . . . . . . .  2

Health Utilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2

Quality-Adjusted Life Years and the Devaluation of Life with Disability 5
Questionnaires Used to “Describe” the Health State, 

and Their Flaws . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2

Valuation of Disability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  2

Calculating QALYs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  3

Example 1: Connie and Bill . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  3

Calculating Cost per QALY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  3

Methodological Flaws of Quality-Adjusted Life Years . . . . . . . . . . . . . . . .  3

QALYs Do Not Fully Measure Health-Related Quality of Life . . . . . . .  3

Palliative Care . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  3

When Health Utilities Are “Zero” . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  3

Distinguishing Between Subgroups of Patients 

with the Same Condition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  3

Accounting for Clinical Knowledge Not Reflected in the 

Research Literature . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  3

Chapter 2: Bioethics and Quality-Adjusted Life Years . . . . . . . . . . . . . . . . . . . . . . . . .  3

Does Disability Reduce Quality of Life? . . . . . . . . . . . . . . . . . . . . . . . . . . .  3

Does the Use of QALYs Discriminate Against People 

with Disabilities? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  4

Chapter 3: Utilization of QALYs in the United States . . . . . . . . . . . . . . . . . . . . . . . . . .  4

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  4

Use of QALYs by the US Federal and State Governments . . . . . . . . . . . .  4

Use of QALYs by Private Health Insurers . . . . . . . . . . . . . . . . . . . . . . . . . .  4

Ethical Concerns with Respect to the Use of QALYs in 

the United Kingdom and Their Relationship to Concerns 

in the United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  4

Alzheimer’s Disease . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  5

Cystic Fibrosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  5

Use of Similar Models in United States National Health 

Insurance Programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  5

Chapter 4: Case Study: CVS Caremark . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  5

Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  5

Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  5

CVS Caremark’s Decision . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  5

6 National Council on Disability
Responses to the CVS Caremark Decision . . . . . . . . . . . . . . . . . . . . . . . . .  5

CVS Caremark’s Response to Criticisms and 

Stakeholder Concerns . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  5

Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  5

Chapter 5: Alternatives to the Use of QALYs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  6

Equal Value of Life Years Gained (evLYG) 

Supplementary Measure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  6

Not Using QALYs When Determining Cost-Effectiveness . . . . . . . . . . . . .  6

Multi-Criteria Decision Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  6

Alternatives to QALYs That Use Primarily Patient Preferences . . . . . . . . .  6

Patient Perspective Value Framework . . . . . . . . . . . . . . . . . . . . . . . . .  6

The Efficiency Frontier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  6

Are There Alternatives to QALYs That Perform the Same 

Functions as QALYs? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  6

Chapter 6: Recommendations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  6

Appendix A: Calculation of QALYs Flowchart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  7

Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .  7

Quality-Adjusted Life Years and the Devaluation of Life with Disability 7
8 National Council on Disability
Acknowledgments

This report is part of a series of reports on bioethics and people with disabilities which was developed 

through a cooperative agreement with the Disability Rights Education & Defense Fund (DREDF). The 

National Council on Disability (NCD) appreciates the work of those who contributed their expertise 

in its development, including Kelly Israel, Policy Analyst, Autistic Self Advocacy Network (ASAN), and 

Samantha Crane, Director of Legal and Public Policy, ASAN. NCD also appreciates the work of Marilyn 

Golden, Senior Policy Analyst, DREDF, who shepherded the entire series in cooperation with NCD. 

We also thank those who participated on the Advisory Panel, in interviews, and in the stakeholder 

convening, whose knowledge and willingness to share information helped make this series possible.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 9
10 National Council on Disability
Executive Summary

Purpose

Healthcare coverage decisions are of vital 

importance to people with disabilities 

and their families. If the medications 

and treatments that extend or improve the lives 

of people with disabilities are not covered by 

insurance, they will not have access to needed 

health care, and will have lower quality of life 

and lower life expectancy. Public and private 

insurance providers 

sometimes attempt to 

limit their healthcare 

spending in ways that 

reduce people with 

disabilities’ access to 

health care. One of the 

means by which they do 

so is by refusing to cover 

(or by limiting access to) healthcare treatments 

based on their cost-effectiveness. One metric 

often used to help calculate cost-effectiveness—

quality-adjusted life years (QALYs)—may have 

a negative impact on the health and welfare of 

people with disabilities.

QALYs are a number which (theoretically) 

represents the degree to which a drug or 

treatment extends life and improves quality 

of life—although quality of life is a difficult 

concept to define, quantify, and measure. 

However, QALYs aggregate quality and quantity 

of life simply by lowering the value of a year of 

treatment by the degree to which an illness, 

disability, or other health condition is perceived 

to harm the person’s quality of life during 

that year.

There has been increasing interest among 

national health insurance programs (like Medicaid), 

private health insurance companies, and pharmacy 

benefit managers (PBMs; managers of drug 

benefits for health 

insurers) in using QALYs 

to inform their decisions 

about which drugs and 

treatments they will 

cover. Many individuals, 

however, have serious 

concerns with the use 

of QALYs.

The use of QALYs has been opposed by 

people with disabilities and disability rights 

advocates for more than 20 years. Their use is 

also opposed by some bioethicists and patient 

rights organizations. These stakeholders fear that 

use of QALYs undervalues vital treatments that 

extend or improve the lives of people with 

disabilities. This is because the QALY calculation 

reduces the value of treatments that do not bring 

a person back to “perfect health,” in the sense of 

not having a disability and meeting society’s 

definitions of “healthy” and “functioning”; uses 

[T]he QALY calculation reduces the 

value of treatments that do not bring 

a person back to “perfect health,” in 

the sense of not having a disability 

and meeting society’s definitions of 

“healthy” and “functioning”

Quality-Adjusted Life Years and the Devaluation of Life with Disability 11
simplified assessments of value that do not 

account for the complexity of patient experience; 

and does not to take into account clinical 

expertise on rare disorders that may not have an 

extensive research literature available for use. 

Other stakeholders—often from the medical, 

health economics, and health insurance fields—

argue that QALYs provide payers with valuable 

information on a treatment’s potential benefits 

and costs and aid them in negotiating a 

reasonable price with the drug (or treatment)’s 

manufacturers.

Although QALYs have not historically 

been utilized for benefits and reimbursement 

decisions in the United States, prominent 

nonprofit corporations 

and professional 

associations are now 

using QALYs to evaluate 

the cost-effectiveness 

of new drugs and 

treatments. These 

evaluations now have 

a strong influence 

on many private and public health insurers’ 

decisions about which drugs and treatments 

they will cover. Additionally, the use of QALYs 

to inform benefits and coverage decisions in 

other countries has limited access to lifesaving 

medications for people with disabilities and 

those with chronic illnesses.

NCD undertook this report to examine 

how use of QALYs may impact people with 

disabilities in the United States and will 

inform Congress and the executive branch 

on the ways in which QALYs impact people 

with chronic illnesses and disabilities’ access 

to treatment and health care. The report 

includes recommendations aimed at ensuring 

that cost-effectiveness assessments of 

drugs and medical treatments, considered 

in benefits and coverage decisions, are fair 

and nondiscriminatory. NCD’s research team 

used multiple methods to gather information, 

including a comprehensive literature review and 

interviews with experts and stakeholders who 

understand how QALYs may impact people with 

disabilities.

Background

Payers in the healthcare context—both private 

health insurance companies (for example, 

Anthem) and public health insurers (for 

example, Medicaid 

and the Veterans 

Administration)—

typically have a limited 

amount of money to 

spend. Payers therefore 

want to fund treatments 

or drugs that are of 

high value and clinical 

effectiveness. For many payers, a high-value 

drug or treatment is equivalent to a costeffective one, but patients may have different 

opinions on what constitutes value.

A cost-effective treatment is generally 

considered to be a treatment for which, from 

the perspective of the payer, the cost of the 

treatment does not outweigh the health 

improvements it provides. QALYs are used as 

one possible measure of the degree to which 

a treatment improves both quality and quantity 

of life. A drug or treatment that provides its 

beneficiaries with more QALYs is considered 

more effective. Therefore, a drug that provides its 

[T]he use of QALYs to inform 

benefits and coverage decisions in 

other countries has limited access 

to lifesaving medications for people 

with disabilities and those with 

chronic illnesses

12 National Council on Disability
beneficiaries with more QALYs for less money is 

considered more cost-effective.

QALYs are used in cost-effectiveness studies, 

in particular a type of cost-effectiveness study 

called a cost-utility analysis (CUA), as well 

as in decision-making tools known as value 

frameworks. Both are relied on by payers as 

a source of evidence of a drug or treatment’s 

cost-effectiveness. The final decision made by 

payers is not dependent on cost-effectiveness as 

measured in QALYs, but instead is informed by it.

Key Findings

■ QALYs have been the subject of 

considerable ethical debate since they were 

first invented. The 

primary ethical 

issues concern 

whether or not 

use of QALYs 

to calculate the 

cost-effectiveness 

of drugs and treatments discriminates 

against people with disabilities and chronic 

illnesses, how exactly they do so, and, 

if they do, whether or not that is ethical. 

There is not universal agreement on 

any of these issues. However, NCD has 

found sufficient evidence of QALYs being 

discriminatory (or potentially discriminatory) 

to warrant concern, including: (1) concerns 

raised by stakeholders in the interviews 

NCD undertook for this report (including 

bioethicists, patient rights groups, and 

disability rights advocates); (2) compelling 

arguments from prominent bioethicists 

condemning the use of QALYs; and (3) 

the inability of patients in countries where 

QALYs are used more heavily to obtain 

coverage of needed health care.

■ The Federal Government does not have a 

single, comprehensive policy on the use 

of QALYs. The Federal Government has 

considered increasing its utilization of costeffectiveness research and rejected the 

idea at different points in its history, leading 

to inconsistent policies across federal 

agencies. Some agencies are banned from 

using QALYs to make benefits and coverage 

decisions, while others use them frequently.

■ There has been increasing interest by 

the Federal Government in reducing the 

cost of health care by 

modeling parts of its 

national health insurance 

programs after the 

healthcare systems of 

other countries, such 

as the United Kingdom. 

Several of these countries utilize QALYs 

to make benefits and coverage decisions. 

The coverage denials and loss of access 

to care faced by people with disabilities 

in these countries illustrate what might 

happen if the United States made a 

similar choice.

■ QALYs and cost-effectiveness research are 

one of many different types of evidence 

insurers consider when making their 

decisions. There is limited publicly 

available evidence that shows to what 

extent private health insurance companies 

use QALYs and cost-effectiveness research 

to inform their medicine and medical 

treatment-related decision making. 

NCD has found sufficient evidence 

of QALYs being discriminatory 

(or potentially discriminatory) to 

warrant concern 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 13
QALYs and the analyses that rely on them 

are most likely utilized in insurers’ internal 

decision-making processes, for which 

there is little transparency.

■ There are alternatives to the use of 

QALYs. These alternatives range from 

well-established methods regularly 

used by United States federal agencies 

already, such as cost-benefit analysis, to 

unexplored but promising alternatives 

such as value frameworks that use patient 

preferences to determine the value of 

healthcare treatments. Many alternatives 

may themselves be discriminatory if used 

in certain contexts, or if they are used 

without paying 

sufficient attention 

to the possibility 

that discrimination 

may occur. 

However, several 

(such as multicriteria decision 

analysis [MCDA], 

which allows its user to consider multiple 

unrelated benefits of a treatment and 

weight each benefit individually before 

arriving at a decision) can be used in a 

nondiscriminatory manner. It is much more 

difficult, if not impossible, to use QALYs 

in a nondiscriminatory manner. No single 

alternative serves all of the functions 

of QALYs.

Key Recommendations

Congress

When enacting health reform bills, Congress 

should:

QALYs and the analyses that rely 

on them are most likely utilized in 

insurers’ internal decision-making 

processes, for which there is little 

transparency

■ Avoid creating provisions of any bill that 

would require the agency with management 

and oversight responsibilities (such as, for 

example, HHS) to cover only the most costeffective drugs and treatments, or to require 

the agency to impose restrictions on less 

cost-effective treatments.

Congress should pass legislation:

■ Prohibiting the use of QALYs by Medicaid 

and Medicare.

■ Provide funding to Health and Human 

Services (HHS) for research on best practices 

on the use of cost-effectiveness to inform 

benefits and coverage decisions with respect 

to US national health insurance programs, 

such as Medicare 

and Medicaid. “Best 

practices” in this case 

refers to a means of 

utilizing cost-effectiveness 

research that facilitates 

greater access to care, 

and does not reduce 

access to care for people with chronic health 

conditions and disabilities.

US Department of Health and Human 

Services (HHS), Office for Civil Rights 

(OCR); US Department of Justice (DOJ) 

Civil Rights Division

DOJ and OCR should jointly issue guidance 

clarifying that the ADA applies to coverage 

programs that states operate such as Medicaid.

OCR, in consultation with DOJ as appropriate, 

should issue guidance to HHS sub-agencies, 

such as the Centers for Medicare and Medicaid 

Services (CMS) as well as to state Medicaid 

agencies, clarifying that:

14 National Council on Disability
Section 504 and Section 1557 also apply 

to Medicaid programs because they 

receive federal financial assistance. The 

guidance should specifically discuss 

how these authorities apply to benefits 

and reimbursement decisions, and that 

payment decisions should not rely on costeffectiveness research or reports that are 

developed using QALYs.

Section 504 and Section 1557 apply to 

health insurance programs operated by 

recipients of federal financial assistance 

from HHS. The guidance should discuss 

that covered health insurance programs 

should not rely on cost-effectiveness 

research or reports that gather input from 

the public on health preferences that do not 

include the input of people with disabilities 

and chronic illnesses.

HHS

■ HHS should consider including explicitly 

recruited people with disabilities and chronic 

illnesses as members of committees and 

working groups formed to develop effective 

healthcare reform and strategies for 

lowering the cost of prescription drugs.

■ HHS should support healthcare providers by 

issuing guidance on what steps to take if their 

patient’s health insurance agency refuses to 

cover recommended treatment on the basis 

of that treatment’s cost-effectiveness.

HHS, OCR

■ OCR should issue guidance to HHS subagencies, such as Centers for Medicare 

and Medicaid Services, State Medicaid 

Agencies, clarifying that:

● Title II of the Americans with Disabilities 

Act (ADA) applies to national health 

insurance programs jointly run by the 

Federal Government and the States, 

such as Medicaid. The guidance should 

specifically discuss how the ADA applies 

to benefits and reimbursement decisions, 

and that payment decisions should not 

rely on cost-effectiveness research or 

reports that are developed using QALYs; 

and

● Insurance programs jointly run by the 

Federal Government and the States, such 

as Medicaid, should not rely on costeffectiveness research or reports that 

gather input from the public on health 

preferences that do not include the input 

of people with disabilities and chronic 

illnesses.

HHS, CMS

■ CMS should utilize well-established 

alternatives to QALYs, such as MCDA, 

which is a method that better acknowledges 

the complexity of healthcare coverage 

decisions, or cost-benefit analysis, when 

the exact benefits and costs of a drug or 

treatment are known. CMS could utilize 

these methods in combination, such 

as using cost-benefit analysis as one 

component of an MCDA. If CMS does 

utilize cost-effectiveness analysis, it should 

consider utilizing it as one component of a 

condition-specific MCDA.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 15
16 National Council on Disability
Acronym Glossary

ADA Americans with Disabilities Act

ASAN Autistic Self-Advocacy Network

CBO Congressional Budget Office

CDC Centers for Disease Control and Prevention

CEA cost-effectiveness analysis

CMS Centers for Medicare and Medicaid Services

CUA cost-utility analysis

DOJ US Department of Justice

DREDF Disability Rights Education & Defense Fund

evLYG equal value of life years gained

FDA US Food and Drug Administration

GDP gross domestic product

HHS Health and Human Services

HTA health technology assessment

ICER Institute for Clinical and Economic Review

IPI International Pricing Index

ISPOR International Society for Pharmacoeconomics and Outcomes Research

MCDA multi-criteria decision analysis

NCD National Council on Disability

NHS National Health Service

NICE National Institute for Health and Care Excellence

OCR Office for Civil Rights

PBM pharmacy benefit managers

PCORI Patient Centered Outcomes Research Institute

PIPC Partnership to Improve Patient Care

PPVF Patient Perspective Value Framework

QALY quality-adjusted life years

VA Department of Veterans Affairs

Quality-Adjusted Life Years and the Devaluation of Life with Disability 17
Some stakeholders, but especially bioethicists 

and people with disabilities, have argued that 

QALYs are built on a faulty premise: that life 

with a disability is inherently worse than life 

without a disability

18 National Council on Disability
Introduction

Healthcare spending has become a major 

concern in policy discussions across the 

United States. Concern is growing in 

large part due to the rapidly rising cost of health 

care. In 1973, healthcare 

spending amounted to 

7.5 percent of US gross 

domestic product (GDP), 

while in 2017, healthcare 

spending more than 

doubled to approximately 

18 percent of US GDP.1

In 1973, the United 

States spent just $102.8 billion dollars2 on health 

care, while in 2017 total US healthcare spending 

had risen to nearly 3.5 trillion dollars.3 In this 

context, policymakers have rightly sought various 

means of lowering total healthcare costs.

One of the major 

means that has been 

considered by healthcare 

policymakers (such as US 

federal agencies, health 

economists, etc.) is the 

idea of health insurers 

and other payers funding “high-value” treatments 

over “low-value” treatments.4 Patients and payers 

may significantly differ in how they interpret 

which treatments are of “high value” to them. 

For many payers, however, a high-value drug 

or treatment is merely a cost-effective one. 

A cost-effective treatment is a treatment that 

significantly extends life or improves patient 

quality of life (or both), at a cost which, to the 

payer, does not outweigh 

the improvements to 

health it provides. Payers 

may rely on a variety of 

evidence to determine 

cost-effectiveness, 

particularly costeffectiveness analysis 

(CEA) studies, which 

examine the cost-effectiveness of drugs and 

treatments.

Several nonprofit organizations and 

professional associations in the United States 

have also attempted to help payers determine 

which treatments are 

of the highest value. 

To this end, they have 

created decision-making 

tools known as value 

frameworks, many of 

which primarily focus on 

cost-effectiveness.5 Value frameworks can be 

used to produce reports that evaluate new drugs 

and treatments (sometimes known as health 

technology assessment reports, or HTAs).6 The 

most influential of these HTAs are produced by 

In 1973, healthcare spending 

amounted to 7.5 percent of US gross

domestic product (GDP), while in 

2017, healthcare spending more 

than doubled to approximately 

18 percent of US GDP

Patients and payers may 

significantly differ in how they 

interpret which treatments are of 

“high value” to them

Quality-Adjusted Life Years and the Devaluation of Life with Disability 19
the Institute for Clinical and Economic Review 

(ICER), whose reports are relied on by payers 

as varied as the pharmacy benefit manager CVS 

Caremark and the Veterans Administration.

In prioritizing cost-effective treatments 

and treating cost-effectiveness as identical to 

value, however, payers may risk using means of 

quantifying which treatments are cost-effective 

that are simplistic and potentially discriminatory, 

such as QALYs.

QALYs are a measure that attempts to show 

the extent to which a particular treatment 

extends life and improves quality of life at the 

same time. QALYs are an important outcome 

measure in several influential value frameworks, 

such as ICER’s value framework. QALYs are also 

used extensively to make healthcare coverage 

and reimbursement decisions in other countries. 

For example, the National Institute for Health and 

Care Excellence (NICE) in the United Kingdom 

uses QALYs when determining what Britain 

and Wales’ single-payer healthcare system, 

the National Health Service (NHS), will cover. 

Health outcomes for some patients with chronic 

illnesses and disabilities (such as patients with 

lung cancer) are notably worse in the United 

Kingdom than in the United States.7

Many stakeholders are therefore concerned 

that the way QALYs are calculated devalues 

treatments that extend the lives of people with 

disabilities, or treatments that mitigate—without 

eliminating—the impact of disability on their 

health. They argue that if value frameworks that 

use QALYs become more influential, people 

with disabilities will lose access to needed care. 

Other stakeholders view QALYs as a way to 

provide necessary information on the benefits 

and costs of healthcare in a healthcare system 

that has been put under strain by rising costs. 

This report examines how QALYs are calculated, 

the bioethical implications of using QALYs, 

and the history of the use of QALYs in the 

United States.

Summary of Methodology

In order to get a clear and comprehensive picture 

of the use of QALYs in the United States, the 

NCD research team consulted bioethicists, 

patient rights advocates, researchers and health 

economists, people with disabilities and their 

families, and relevant scholarly articles from 

bioethical, economic, insurance agency, and 

healthcare system perspectives.

Qualitative Data

To understand how the quality-adjusted life year 

was used by payers and to better inform the 

conclusions reached, NCD conducted seven 

in-depth interviews with disability rights 

advocates, representatives of advocacy 

organizations who serve patients, two 

bioethicists with a significant understanding 

of the ethical issues presented by QALYs, a 

representative of an organization that reviews 

value frameworks to determine their degree of 

patient-centeredness, and a representative of 

the nonprofit Institute for Clinical and Economic 

Review, which uses QALYs. Additionally, 

the research team conducted a stakeholder 

convening on September 24, 2018 to inform and 

aid NCD in the initial development of this report.

Literature Review

To obtain information on how QALYs are used, 

as well as the perspectives and opinions of 

ethical experts and experts in the field of health 

20 National Council on Disability
economics on its use, NCD reviewed articles 

from research journals, bioethics journals, 

and news articles pertaining to the use of the 

quality-adjusted life year. NCD also conducted 

an in-depth review of several value frameworks, 

including FasterCures’ Patient Perspective 

Value Framework, ICER’s Value Assessment 

Framework, and the condition-specific decisionmaking tools created by the Innovation and 

Value Initiative.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 21
22 National Council on Disability
Chapter 1: How QALYs Are Calculated and the Impact 

on People with Disabilities and Patients with Chronic 

and/or Degenerative Illnesses

The Purpose of QALYs

I

n order to understand how to calculate QALYs, 

it is important to explain both what QALYs are 

supposed to represent, and why they are used.

What QALYs Represent

Normally, when a researcher or scientist tries to 

determine whether or not a healthcare treatment 

(like chemotherapy) improves health, they are 

looking at one of two different things:

■ whether the treatment extends the patient’s 

life, or

■ whether the treatment improves the quality 

of the patient’s life.8

While measuring whether or not a treatment 

extends life is fairly straightforward, measuring 

the degree to which a treatment improves 

someone’s quality of life is more complicated. 

The portion of a person’s quality of life that 

relates to their health is called their health-related 

quality of life.9

Health-related quality of life is a broad 

concept. According to the Centers for Disease 

Control and Prevention (CDC), at the individual 

level, it may include a person’s mood and 

energy levels, their physical and mental health, 

and the elements of the person’s life that 

contribute to these factors—such as some 

aspects of the person’s disabilities, health risks, 

and their social and socioeconomic status. 

If measured at the population level, it includes 

any “conditions, policies, and practices that 

influence a population’s health perceptions and 

functional status.”10 Health researchers and 

government agencies (including the CDC itself, 

by conducting population-level surveys using 

a set of 14 questions called “Healthy Days 

Measures”)11 have created different means of 

measuring health-related quality of life.

When healthcare payers decide how to spend 

their money, they are often looking for some way 

to represent all the benefits a particular treatment 

provides at once, as this saves them time. 

However, studies of treatments tend to measure 

benefits of treatment that are qualitatively 

different from one another, such as life extension 

and quality of life, separately from one another. 

For example, a study could measure the length 

of time a patient survives after treatment, or the 

number of days the person is free from pain, 

but perhaps not both in the same study.12 It may 

be difficult, therefore, to directly compare the 

value of a treatment that primarily extends life to 

the value of a treatment that primarily improves 

quality of life.13

QALYs are one attempt to get around this 

problem. QALYs are the product of an equation 

designed to “combin[e] the effects of health 

interventions [treatments] on morbidity [quality 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 23
of life] and mortality [quantity of life] into a single 

index.”14 The QALY equation does this in a rather 

simplistic fashion. It simply lowers the value of a 

year of treatment by the degree to which an 

illness or disability is perceived to harm the 

person’s quality of life during that year.15 QALYs 

typically are calculated before and after treatment 

to determine the degree to which a treatment 

improves the number of QALYs gained by the 

patients being studied.16

QALYs are calculated by multiplying a decimal 

number between 0 and 1, which represents a 

person’s health-related quality of life, by a number 

representing quantity of life. The “quantity” can 

be the number of years 

by which the treatment 

extends life, the number 

of years a person expects 

to have to take the 

treatment, the amount 

of time a person has 

left to live, or any other 

time period relevant 

to the researcher. A 

typical QALY calculation 

is shown in the “QALY 

Calculation” box.

Ari Ne’eman, a disability rights advocate and 

expert on QALYs, described what QALYs are and 

what they do in this way:

The QALY works by weighting the lives 

of people with disabilities: If we were to 

assign autism a disability weight of 0.2, that 

[number] would mean that a year in the life of 

an autistic person would be worth 80 percent 

of a nondisabled person’s life. Different 

disabilities would get a different number, if 

you assigned 0.5 to a mobility impairment, 

then a year in that person’s life would equal 

50 percent of a nondisabled life year.

A flowchart showing how QALYs would be 

calculated if the researcher or scientist used a 

commonly utilized questionnaire—the EQ-5D—is 

included as Appendix A of this report.

Why QALYs Are Used

Why would it be necessary to measure both 

quantity of life and health-related quality of life 

at the same time? The most frequently provided 

explanations in research literature for the use of 

QALYs are: (1) to compare 

the impact of multiple 

treatments for unrelated 

conditions to one another; 

or (2) to assess whether 

a new treatment or drug 

would be more costeffective than the drug or 

treatment that is currently 

being used.17

This report focuses on 

the most common use 

of QALYs: their use by 

health economists, researchers, and nonprofits 

to perform cost-effectiveness analyses (CEAs) 

and health technology assessments (HTAs); the 

“The QALY works by weighting the 

lives of people with disabilities: If 

we were to assign autism a disability 

weight of 0.2, that [number] would

mean that a year in the life of an 

autistic person would be worth 

80 percent of a nondisabled person’s 

life. Different disabilities would get

a different number .

QALY Calculation

Number between 0 and 1 representing 

quality of life of x number of years = number 

of QALYs

24 National Council on Disability
subsequent use of CEAs and HTAs by private and 

public health insurers to determine what drugs 

or treatments they will fund; and the real and 

potential negative impact CEAs and HTAs have 

on people with chronic illnesses and disabilities’ 

access to physician-recommended drugs and 

treatments.

Cost-Effectiveness Studies

Cost-effectiveness studies are designed to 

compare various healthcare treatments to each 

other and determine whether the benefits of a 

healthcare treatment are worth the treatment’s 

cost. The type of cost-effectiveness study that 

uses QALYs is called a cost-utility analysis 

(CUA).18 In a CUA, 

the number of QALYs 

gained from treatment 

is a measure of the 

“health outcome,” or 

the overall benefit of the 

treatment.

The difference 

between the cost-effectiveness of the 

treatment being examined and another 

treatment being examined by the researcher 

(typically, the treatment currently in use) is 

referred to as the treatment’s incremental 

cost-effectiveness ratio, or “ICER.”19 The 

ICER is often used when comparing the costeffectiveness of multiple treatments.20 When 

using QALYs, the ICER is often referred to as 

the treatment’s “cost per QALY,” although it is 

possible to get the “cost per QALY” of a single 

treatment.21 At its most simple, it is important 

to know that the lower the cost per QALY, the 

more cost-effective the treatment is considered 

to be.

QALYs are also used in some of the 

decision-making tools known as “value 

frameworks.” When QALYs are used in a 

value framework, it is typically because CUA 

studies are used as evidence of the benefits 

and costs of the treatment being evaluated 

by the report. Use of the report can mean 

that, instead of having to weigh any number 

of complex considerations relating to whether 

or not a treatment should be covered, payers 

can simply fund the treatment that has a better 

“cost per QALY,” according to its corresponding 

report. CUAs and other QALY-based reports 

and research studies are not healthcare policies 

in and of themselves, but rather are used to 

inform the development 

of healthcare policies 

(for example, insurers’ 

drug formularies).

Calculation of 

Quality-Adjusted 

Life Years

While the equation used to calculate QALYs 

is always the same, there is no one single 

way to calculate the numbers that go into 

that equation. For instance, there are many 

different ways to calculate the number 

between 0 and 1—often called the “health 

utility”—that represents health-related quality 

of life. However, there are common methods 

typically used by many health economists and 

researchers employing QALYs in CUA studies. 

Many components often used to calculate 

QALYs are used internationally. The EQ-5D,22

a questionnaire frequently used to calculate 

QALYs, is used in countries as diverse as the 

United Kingdom,23 Iran,24 and China.25

The EQ-5D, a questionnaire 

frequently used to calculate QALYs, 

is used in countries as diverse as 

the United Kingdom, Iran, and 

China

Quality-Adjusted Life Years and the Devaluation of Life with Disability 25
Health Utilities

To calculate a QALY, it is necessary to determine 

by how much not being in perfect health impacts a 

person’s quality of life. QALYS do this by assigning 

a number between 0 and 1, called a health utility, 

to the various conditions a person’s health could 

be in (often called “health states”).26 A 0 would 

represent the lowest possible quality of life, while 

a 1 would represent the highest possible quality 

of life. Health states are represented by points on 

the scale of 0 to 1—for example, 0.2, 0.5, 0.8.

Health utilities are 

typically derived from 

surveys, which attempt 

to determine how much 

survey participants would 

prefer to be in one health 

state as compared to 

another. Health states do 

not correspond directly to 

specific disabilities—they 

instead represent the 

degree of impairment 

a person has in specific, limited categories of 

functioning (such as mobility, ability to perform 

tasks, etc.). However, most disabilities share 

some or all characteristics of a health state. 

Therefore, the goal of a “health utility” is, in 

effect, to measure the degree to which having a 

particular form of a disease or disability, such as 

“having late-stage cancer” or “having a specific 

type or degree of type 2 diabetes,” is viewed as 

negatively impacting quality of life as compared 

to a state of perfect health.27

Questionnaires Used to “Describe” 

the Health State, and Their Flaws

As noted above, the first thing the researcher 

has to do is determine how having a disability 

or illness impacts a person. Typically, in order 

to obtain this information, the researcher has a 

sample of patients with the illness, condition, 

or disability fill out a survey or questionnaire.28

There is no one, single definitive questionnaire 

or survey that is used.29 The most common 

questionnaire is the EQ-5D.30 The EQ-5D is 

extremely popular internationally.31

The EQ-5D takes an extremely limited 

approach to measuring “quality of life.” Use of 

the EQ-5D requires patients to rate the degree 

to which they have 

“problems” with only 

a few extremely broad 

categories of “physical, 

cognitive, or social 

functioning,” rather than 

the myriad of effects 

someone’s health could 

have on their quality 

of life.

The EQ-5D surveys 

patients’ health as it 

relates to five “dimensions” of quality of life: 

mobility, self-care, usual activities, pain/

discomfort, and anxiety/depression.32 These five 

categories do not measure the wide variety of 

impacts a disability or illness could have on 

quality of life. NCD interviewed the bioethicist 

Joseph Stramondo, who said “I think that, 

while there is a relationship between disability 

and quality of life, it is extremely variable, 

and impossible to generalize. There are all 

kinds of things [about disability and illness] 

that impact quality of life on a case-by-case 

basis: relationships, income, accessibility 

considerations.” Moreover, neither “self-care” 

nor “usual activities” are defined in detail 

anywhere in the sample questionnaires available 

Use of the EQ-5D requires patients 

to rate the degree to which they 

have “problems” with only a 

few extremely broad categories 

of “physical, cognitive, or social 

functioning,” rather than the myriad 

of effects someone’s health could 

have on their quality of life

26 National Council on Disability
on the EQ-5D website, meaning that many 

patients may not know what these terms mean 

for them. Furthermore, there is no way to 

account for external factors, like the availability 

of reasonable accommodations or the 

accessibility of the built environment, as a factor 

in the assessment of quality of life with a 

disability, despite the fact that these factors play 

a significant role in determining the life 

experience of many people with disabilities.

Impacts on these dimensions are then rated 

by “severity.” Different 

forms of the EQ-5D 

exist. The oldest and 

most commonly used 

form, the EQ-5D-3L,33

assigns three “levels of 

severity” to each of the 

five dimensions. For each 

dimension, it is possible 

for the person taking 

the survey to respond 

“I have no problems,” 

“I have some problems,” 

or “I have extreme problems.”34 For example, 

the EQ-5D-3L User Guide includes the following 

sample question on mobility:

Questions Asked on the EQ-5D-3L 

Questionnaire

Mobility

■ I have no problems in walking about

■ I have some problems in walking about

■ I am confined to bed

“I think that, while there is a 

relationship between disability and 

quality of life, it is extremely variable, 

and impossible to generalize

There are all kinds of things [about 

disability and illness] that impact 

quality of life on a case-by-case basis: 

relationships, income, accessibility 

considerations.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 27

Note that this question is focused on whether 

a person has problems “walking about,” and 

the most severe problems are described as the 

person “being confined to bed.” The questions 

do not appear to consider the possibility that a 

person who cannot “walk about” can still move, 

such as a person who cannot walk but who can 

use a wheelchair.

Nor does the EQ-5D consider the possibility 

that a person who can walk may nevertheless 

have significant trouble leaving the home due 

to other concerns, such 

as the need to stay near 

medical equipment, 

concerns about exposure 

to infections, or 

agoraphobia.

As noted by 

Stramondo and a 

colleague in an article 

on disability and its 

relationship to quality 

of life, impairment in 

performing a specific 

task may have no relationship to quality of life.35

The questionnaire assumes that a person will 

experience difficulty with walking as a significant 

barrier to subjective quality of life when, in fact, 

this is not true of many people with mobility 

impairments. Although there are several 

versions of the EQ-5D, and other versions do 

not phrase the question and/or questions in this 

manner, the other versions also assume that 

being unable to walk has a severely negative 

impact on quality of life.36

In the EQ-5D-3L, each dimension receives a 

score from 1 to 3, where one is the best possible 

score and 3 is the worst possible score. Thus, a 

person who checked the first box, “I have no 
problems,” would be assigned a score of 1 for 

mobility.37 Filling out the entire questionnaire 

generates a series of five numbers, each of 

which is between 1 and 3. For example, a score 

of 11111 means the person is in perfect health, 

whereas a score of 11223 means the person 

has no problems with the first two dimensions, 

some problems with the next two, and extreme 

problems with the final dimension.38

When using the EQ-5D-3L to calculate 

QALYs, it is this series of five numbers which 

was actually evaluated, as opposed to the actual 

disability and the actual 

effect of the disability on 

physical or psychological 

functioning as reported 

by people with that 

disability. The people 

who decided the value 

of life with a particular 

condition only saw those 

five numbers and/or a 

description of what those 

numbers meant.39

Aside from 

the dehumanizing 

implications of 

disability’s impact on quality of life being 

reduced to a series of five numbers, if two 

different disabilities had exactly the same impact 

on physical or psychological functioning, they 

would have exactly the same health utility value 

for the purpose of calculating QALYs—even if 

they had other differences that some people 

may consider relevant to “quality of life.” The 

numbers are based only on the disability or 

illness’ impact on “physical, psychological, 

cognitive, social or other kinds of functioning,”40

as defined by the survey.

Patients with two conditions with 

the same utility value may have 

very different opinions about which 

aspects of their conditions are most 

important to address, and what 

kinds of treatments would most 

improve their lives. Nonetheless,

treatments that improved their 

health utility scores to the same 

degree would be treated as having 

the exact same value to the patients

Patients with two conditions with the same 

utility value may have very different opinions 

about which aspects of their conditions are 

most important to address, and what kinds of 

treatments would most improve their lives. 

Nonetheless, treatments that improved their 

health utility scores to the same degree would 

be treated as having the exact same value to the 

patients. For example, patients with Disability A 

could place a higher value on reducing pain and a 

lower value on reducing anxiety and depression. 

Patients with Disability B could place a lower 

value on reducing pain 

and a higher value on 

reducing anxiety and 

depression. If patients 

with these disabilities 

received the same 

average EQ-5D score, a 

treatment that reduced 

pain would be treated as 

if patients with Disability 

B valued it to the same 

degree as patients with 

Disability A.

Most other 

questionnaires share 

similar issues. For example, the SF-6D looks at 

the impact of an illness or disability on “physical 

functioning,” the degree to which one’s emotional 

problems limit their ability to perform daily tasks, 

and so on, and uses specific, narrow questions 

to determine the impact.41 Additionally, using 

different questionnaires results in different 

numbers of QALYs, which raises validity and 

reliability concerns, when different methods 

produce results that are not comparable.42

The validity of these generic questionnaires 

can be called even further into question by the 

28 National Council on Disability
fact that the utility values are often not calculated 

separately for each individual cost-effectiveness 

study. Instead, the utility values are often based 

on the outcome of specific past studies in 

which members of the general public valued a 

sample of the possible health states (with values 

for the health states not valued determined 

mathematically from the values of the health 

states that were valued).43 The EuroQoL group, 

maker of the EQ-5D, refers to these studies as 

“value sets.”44

Valuation of Disability

Regardless of how the 

impact is assessed, 

once the researcher 

assesses the impact of 

a health condition on 

health, the researcher 

needs to determine 

how much “worse” it is 

to be in that condition 

as compared to perfect health. This is done by 

determining the degree to which a group of 

people would prefer to be in that health state as 

compared to perfect health.

The researcher can either measure the 

preferences of patients with the disability 

or measure the preferences of the general 

population.45 While there are those in the field 

that advocate for using “patient preferences”46

and those who advocate for using “population 

preferences,”47 the overwhelming majority of 

studies use the preferences of members of the 

general population (76 percent, according to 

one study).48

The preferences of the general population 

are typically calculated by surveying a sample of 

the general public and asking them a series of 

[U]sing different questionnaires 

results in different numbers of 

QALYs, which raises validity and 

reliability concerns, when different 

methods produce results that are 

not comparable

Quality-Adjusted Life Years and the Devaluation of Life with Disability 29

questions. Researchers performing a CUA ask 

a person to imagine a hypothetical situation and 

respond to questions about that hypothetical 

situation. There are two types of questions 

researchers typically ask the public: Time 

Trade-Off questions and Standard Gamble (SG) 

questions.49

In a Time Trade-Off, survey participants are 

asked to determine how many years of living 

with a particular disability (for example, 70 years 

of blindness) they would trade for a shorter 

number of years spent in perfect health (for 

example, 50 years of 

perfect health).50 In a 

Standard Gamble, the 

participants are asked 

to imagine having a 

disability and then 

are asked whether 

they would undergo a 

procedure that had, for 

example, a 50 percent 

chance of returning them to perfect health and a 

20 percent chance of instantly killing them.51

If members of the public respond in a way that 

suggests that they see 20 years in a health state 

corresponding to a specific type of blindness and 

17 years of perfect health as having the same 

value, the researcher will divide 17 by 20 to get 

a health utility value of 0.85 for the health state 

corresponding to that specific type of blindness.52

Many would contend that members of the 

general public do not accurately understand the 

experience of life with a disability and will 

systematically underestimate the value of 

disabled quality of life. However, surveying people 

with disabilities poses other problems. Since 

people with disabilities tend to rate their quality of 

life as higher than the perception of it from the 
general public, leading to lower health utilities, the 

use of survey responses from people with 

disabilities will increase the value of life-extension 

while reducing the value of quality of life 

improvements. Because the QALY compresses 

these two factors into a single number, it forces a 

choice between prioritizing life extension and 

quality of life improvement. In one article, 

bioethicists referred to QALYs’ inability to 

simultaneously value treatments that extend and 

improve the lives of people with disabilities as 

“the QALY trap.”53 According to Ne’eman, this 

problem can be substantially mitigated or 

eliminated by using diagnosis- or domain-specific 

measures, such as lung 

function, pain scales, or 

functional skills, since 

these do not conflate 

morbidity and mortality 

into a single number. As 

Ne’eman stated in his 

interview with NCD:

If you go with a system [for calculating 

QALYs] that surveys the general public, you 

are likely to end up with more resources 

willing to be spent on disability or disease 

mitigation. If you survey [people with 

disabilities], you’re likely going to end up 

with more going to life extension. But it 

forces you to choose. Then you should 

ask—is this a good system?

This speaks to one of the fundamental flaws 

of the QALY: that the conflation of life extension 

and quality of life improvement benefits into a 

single number forces people with disabilities into 

a cruel trap: picking whether they would rather 

live longer or have improved quality of life, when 

In one article, bioethicists referred to 

QALYs’ inability to simultaneously 

value treatments that extend and 

improve the lives of people with 

disabilities as “the QALY trap.

both are entirely feasible in a society willing to 

invest sufficient resources.

Dr. Steve Pearson, bioethicist at the National 

Institutes of Health and the President of ICER, 

agrees that surveying only people with the 

condition is problematic, but surveying the 

healthy community is also problematic unless 

they are informed about the conditions they are 

judging. According to Dr. Pearson,

In order to get the best information, they 

[the healthy community] need to know 

what it is like to live with that condition. You 

want to know if their opinion on how bad 

something is, is higher 

or lower or the same 

as the person who 

actually does have the 

condition. . . . Maybe 

the healthy person, 

with no knowledge 

of the condition, 

would think the opposite of the person 

with the condition. Maybe they think it is 

not so bad having psoriasis, maybe it’s a 

skin rash that’s not so bad. But then you 

talk to a person with psoriasis and they 

say, “It’s awful—you never want to have 

this! It’s painful—you have no idea.” . . . 

Though there are hypothetical and ethical 

reasons people tend to still use the healthy 

community, it still should be informed by 

the patients.54

David Wasserman, a bioethicist at the 

National Institutes of Health, also agrees with 

the limitation of surveying only people with 

the conditions, but believes that surveying the 

healthy community, even when they are provided 

30 National Council on Disability
with information about the condition, is not 

effective. According to Wasserman,

Public opinion is extremely labile. It’s 

influenced by a lot of factors like media 

presentation, exaggerated optimism, 

occasionally by excessive skepticism, by 

poignant anecdotes . . . so, I don’t think that 

you can generally trust popular judgments. 

Even carefully elicited popular judgments 

have serious problems. One approach is 

that we should rely on the preferences 

of the general public about health states, 

but the general public doesn’t have the 

health states in question, so let’s give them 

information on how people in those health 

states regard them. But even if you give 

them that information, they will almost 

surely disregard it. . . .55

Calculating QALYs

The method for calculating QALYs is best 

expressed using an example. This example 

additionally demonstrates one of the primary 

ethical objections to the use of QALYs.

Example 1: Connie and Bill

Connie has a disability. People with Connie’s 

disability have difficulty performing daily living 

tasks and lose the ability to walk. Connie now 

uses a wheelchair for mobility, as do most people 

with Connie’s disability. Without treatment, 

people with Connie’s disability have 4 years 

left to live after they are diagnosed. Based 

on the responses of patients with Connie’s 

disability to the EQ-5D, researchers have 

calculated the health utility, or value of a life with 

Connie’s problems with daily living and need 

for a wheelchair, as 0.5. To get the number of 

quality-adjusted life years she would get from 

living for 4 years with her disability, one must use 

the following equation:

0.5 (health utility) × 4 (the number of years 

Connie has left to live) = 2 QALYs

Thus, the 4 years people with Connie’s 

disability are expected to live without treatment 

would be valued at only 2 QALYs.

A drug that is found that would extend 

the life of people with Connie’s disability by 

20 years, but it would not remove or reduce 

the impact of the disability on daily living; they 

would still use wheelchairs. The health utility 

of their condition is still 0.5. Thus, Connie’s 

life expectancy with treatment is valued at 

10 QALYs. This can be expressed via the 

following equation:

0.5 (utility value) × 20 (the number of years 

Connie would have to live if the treatment 

for patients with her disability was covered) = 

10 QALYs

If people with Connie’s disability were the 

only patient demographic that needed health 

care, the treatment that people with Connie’s 

disability needed would probably be considered 

cost-effective for the insurer because these 

individuals would gain 8 QALYs from being 

treated.

However, there is another patient, Bill. Bill 

has a medical condition that also has a health 

utility of 0.5 and that causes patients with that 

disability to need a wheelchair. Patients with Bill’s 

disability will only live for another 4 years without 

treatment, and would also gain only 2 QALYs 

during those 4 years without treatment.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 31
There is a drug that would extend the lives of 

these patients to 20 years, but would also raise 

their quality of life back up to 1—the utility value 

for “perfect health.” This would mean that Bill 

and other patients with his disability would no 

longer have difficulty with daily living tasks and 

no longer need a wheelchair. This can be shown 

using the following equation:

1 (health utility) × 20 (the number of years 

Bill could live if the treatment for patients 

with his disability was covered) = 20 QALYs

Given that patients with Bill’s condition will 

gain 18 QALYS from being treated as compared 

to patients with Connie’s condition, who would 

only gain 8 QALYs, the drug for patients with 

Bill’s condition will be considered more costeffective than the drug for patients with Connie’s 

condition. For the purposes of this example, the 

two treatments cost exactly the same amount of 

money, and the payer only has enough money to 

pay for one of these two treatments at this time. 

If the payer relies on QALYs to determine how 

cost-effective the two drugs are, the payer will 

favor covering the treatment patients with Bill’s 

disability need over the treatment patients with 

Connie’s disability need.

In an environment with scarce resources, 

Bill’s condition will be more likely to have 

treatments for it funded than Connie’s. While 

these decisions are typically made at the 

population level, rather than in relation to 

specific patients, they create an environment 

of systemic inequality, where people with 

disabilities and chronic conditions that will be 

managed, rather than cured, are less likely 

to receive access to treatment under health 

systems that ration care utilizing the QALY.

Calculating Cost per QALY

When trying to decide whether to cover a 

treatment, most payers are interested in the 

“incremental cost-effectiveness ratio,” which is 

typically the difference between the costeffectiveness of the treatment that is being 

studied as compared to another treatment 

(which is often either another possible treatment 

for the same illness or problem, a placebo, or 

the standard therapy that is currently in use).56

In the box “Cost per QALY,” “ICER” stands for 

incremental cost-effectiveness ratio. As explained 

above, the ICER is often referred to as the “cost 

per QALY,” although the cost per QALY of a 

single treatment can theoretically be calculated. 

One can calculate the ICER by using this 

formula.57

Cost per QALY/ICER

In this formula, C means “Cost,” C1 

represents the treatment being studied, and 

C0 represents either the current treatment 

or another treatment being considered for 

coverage. E means “Effect,” E1 represents 

the number of QALYs gained from the 

treatment being studied, and E0 represents 

the number of QALYs gained from either 

the current treatment or another treatment 

being considered for coverage. To obtain the 

“cost per QALY” of a single treatment rather 

than an ICER (although this is less common), 

divide the treatment’s cost by the number of 

QALYs gained from treatment.

32 National Council on Disability
Some payers have a specific threshold costper-QALY. For example, a payer could decide that 

they will not cover any treatment that costs more 

than $50,000 per QALY.

Methodological Flaws of 

Quality-Adjusted Life Years

QALY calculations are subject to several 

methodological flaws that seriously undermine 

their use as a fair method of comparing the 

relative value of treatments.

QALYs Do Not Fully Measure 

Health-Related Quality of Life

One significant flaw of QALYs is simply that 

they do not measure what their proponents 

claim they measure: 

the combined impact 

a treatment has on life 

expectancy and quality of 

life. As discussed in the 

section “Questionnaires 

Used to ‘Describe’ 

the Disability and Their Flaws,” the generic, 

population preference-based questionnaires 

often used to calculate QALYs only measure a 

few specific impacts of health on quality of life, 

such as pain or anxiety/depression, and may 

not measure these accurately and in a way that 

fully considers the possible accommodations 

available to a person with a disability. This means 

that QALYs undervalue treatments that affect 

aspects of quality of life other than what they 

specifically measure. For example, many people 

with psychiatric disabilities report significant side 

effects associated with certain medications, 

like tardive dyskinesia or weight gain. QALY 

calculations might not value medications that 

allow people with disabilities to avoid these 

This means that QALYs undervalue 

treatments that affect aspects of 

quality of life other than what they 

specifically measure

side effects, since they focus only on measures 

surrounding the mitigation of the primary 

condition rather than the complex context 

surrounding that individual’s life.

Similarly, the level of quality of life experienced 

by a person with a disability or patient may shift 

dramatically based on nonhealth factors, such as 

the availability of reasonable accommodations 

or the accessibility of the built environment. For 

example, the impact of a mobility impairment on 

quality of life is significantly altered based on the 

availability of a wheelchair and a built environment 

that encompasses ramps. Similarly, the impact of 

a cognitive disability is significantly altered based 

on the availability and quality of special education 

services. Typically, the use of QALY assessments 

in healthcare contexts 

do not consider these 

factors, which may 

play an equal or greater 

role in quality of life 

than a purely medical 

assessment. Additionally, 

the utility values used to describe the extent 

to which a disability impacts quality of life are 

derived from people without disabilities, who 

often have prejudices and biases that lead them 

to drastically undervalue life with a disability.

Palliative Care

Failure to consider all aspects of quality of life, 

combined with the weighting of quantity and 

quality of life simultaneously, may lead QALYs to 

undervalue treatments that are purely palliative in 

nature. The main purpose of palliative care is to 

alleviate the pain and suffering of a person who 

has a serious and/or life-threatening illness. Often, 

these illnesses are expected to lead to death, 

as in the case of late-stage cancer or kidney 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 33
disease.58 Palliative care may include treating 

pain, fatigue, reducing the difficulty the person 

has sleeping, or reducing the amount of anxiety 

and depression experienced by the person.59

The first problem is simply that palliative care 

patients often are not expected to live for many 

more years. Since QALYs measure both quality

and quantity of life in the aggregate, and palliative 

care rarely improves a patient’s life expectancy, a 

patient cannot expect to gain many QALYs from a 

palliative care treatment.60

The second problem is that there are things 

that are very important to palliative care patients’ 

evaluation of their own quality of life—such as 

spiritual contentment and personal dignity—

that are rarely if ever measured by the generic 

questionnaires (such 

as the EQ-5D) used to 

calculate QALYs.61 This 

may mean that palliative 

care is undervalued 

as compared to other 

treatments.

Finally, QALYs 

assume that the value 

of a year of life to the patient is the same 

regardless of when that year is lived, which most 

studies have found is simply not true, from the 

patient’s perspective. Patients with a limited 

number of years left to live typically value a year 

much more highly than people who have many 

more years left to live.

Dr. Steve Pearson disagrees with the concern 

that, due to their design, QALYs may undervalue 

palliative care treatments and treatments that 

mitigate the impact of a disabling condition, but 

do not cure it or extend the patient’s life. Pearson 

told NCD that the QALY would do exactly the 

opposite, and that,

Failure to consider all aspects of 

quality of life, combined with the 

weighting of quantity and quality of 

life simultaneously, may lead QALYs 

to undervalue treatments that are 

purely palliative in nature

We [the Institute for Clinical and Economic 

Review] did a cost-effectiveness analysis of 

outpatient palliative care that showed it was 

cost-saving. When something is cost-saving 

you don’t do cost-effectiveness analysis 

per se, but the thing about palliative care 

is that it improves quality of life without 

extending life—although some palliative 

care does, and the sicker you are the better 

that will look, in some sense, because if you 

are already quite well there’s not much to 

palliate . . . the QALY was built to capture 

improvement in quality of life of that type.

Pearson thinks that “the question is which is 

the more cost-effective way to provide pain 

control for [people who 

are] dying, not whether 

we [as a society] should 

or shouldn’t.”62 This may 

be the case if the costeffectiveness of palliative 

care treatments were 

being compared to 

hospitalization (or another 

high-cost, low-value treatment for the patients 

who typically utilize palliative care) or only to 

other palliative care treatments. It is, however, 

difficult to know if this would be true if palliative 

care treatments were competing with other uses 

of the same funds, at the budgeting level.63 Even 

researchers who support the use of QALYs in 

palliative care note that “the brevity of lifespan 

affected results in palliative care yielding a 

fraction of a QALY unit,” and that the use of 

QALYs to help allocate healthcare funding means 

that new palliative care treatments are always 

competing with alternative uses of the same 

money.64 While payers are not attempting to 

34 National Council on Disability
determine whether pain care for the dying is 

“worth it,” they may be attempting to determine 

whether improving pain care is, as compared to 

some other use of their limited funds.

Additionally, researchers who are interested 

in utilizing QALYs for palliative care typically 

propose modifying the standard QALY, either 

by using palliative care-specific questionnaires 

that do evaluate the quality of life aspects 

most important to palliative care patients or by 

incorporating their higher valuation of time spent 

at the end of life into the calculation.65 Other 

researchers propose only comparing end-of-life 

treatments to other end-of-life treatments.66

The need to modify the standard QALY to 

work for palliative care indicates that QALYs are 

unsuitable without modifications. There are likely 

many other specific diseases and circumstances 

for which the use of QALYs is unsuitable without 

modifications, which undermines the claims of 

those who state that QALYs are a metric that can 

be used to compare the 

value of treatments for 

unrelated conditions.

When Health 

Utilities Are “Zero”

QALYs could produce 

problematic results if a 

treatment extends the life 

but does not significantly 

improve the “quality 

of life” (as measured 

by QALYs), of a patient 

whose life’s worth has 

been measured as 0, close to 0, or less than 0. 

In these cases, even the cheapest treatments 

to extend life would not be considered “costeffective” according to a cost-per-QALY standard. 

There are likely many other specific 

diseases and circumstances 

for which the use of QALYs is 

unsuitable without modifications, 

which undermines the claims 

of those who state that QALYs 

are a metric that can be used to 

compare the value of treatments 

for unrelated conditions

When Health Utilities Are Less 

Than 0

Patients with Life-Threatening Condition Y fill 

out the EQ-5D questionnaire and get a score 

of 33333. Solely in this example, members 

of the general population who performed 

a Time Trade Off decided that the utility 

value of this health state (and by extension, 

therefore, Life-Threatening Condition Y) 

was 0. Treatment 1 would extend the lives 

of patients with Life-Threatening Condition 

Y by a year. However, the following simple 

equation illustrates that these patients would 

nonetheless obtain 0 QALYs:

0 (health utility) X 1 (number of years by 

which Treatment 1 extends their life) = 0 

QALYs

This is due to the way 

that QALYs aggregate 

quality of life and quantity 

of life. “When Health 

Utilities Are Less Than 

0” explains how this can 

happen in more detail.

For example, if the 

health utility of having a 

particular disease or 

disability is measured as 

0 or negative, it may 

inevitably lead to the conclusion that the person 

is “better off dead” and that treatments that 

prolong such a life are not cost-effective.67 Such 

an outcome would only be acceptable if a 

person were in a health state in which everyone 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 35
would agree that continued life has no value. 

However, as the bioethicist Stephen Barrie 

noted, the meaning of the “zero” on the health 

utility scale is ambiguous and patients do not

always agree that continued life in a health state 

that earns very low or 

even 0 QALYs has no 

value. A score of 0 

QALYs has meant “being 

dead,” “dying,” and 

“worst possible health 

state,” depending on the 

study and who was 

doing the calculating—

and these are three very 

different things.68 Some individuals may believe 

“dying” is worse than “being dead.” Some 

people with a health state that has been judged 

to be the “worst possible” may wish to 

discontinue treatment, while others may still 

highly value an additional year of life. QALYs do 

not make these distinctions—researchers using 

them would need to treat all three health states 

as equally valueless.

Distinguishing 

Between Subgroups 

of Patients with the 

Same Condition

Some individuals 

argue that QALYs 

do not distinguish 

between subgroups of 

patients with the same 

condition. Subgroups of patients include but 

are not limited to patients of different races/

ethnicities, patients with different genders 

or ages, and patients with other co-occurring 

illnesses.69

A score of 0 QALYs has meant 

“being dead,” “dying,” and “worst 

possible health state,” depending 

on the study and who was doing 

the calculating—and these are three 

very different things

QALYs often rely on research that 

does not adequately account for 

the ways in which many people—

especially, though not exclusively, 

those with rare conditions—may 

have medication responses that vary 

dramatically from the average 

Differences between patient subgroups may 

have a significant impact on the outcome of 

a CUA study. One study, which reviewed 200 

of the 642 English-language CUAs in the Tufts 

Medical Registry, found that only 19 percent of 

these studies reported 

on any differences 

between subgroups.70

Additionally, most 

studies only reported 

differences based on 

age.71 The authors 

hypothesized that failure 

to account for subgroup 

differences may lead to 

payers funding treatments that are of relatively 

low value or even harmful to some subgroups.72

Additionally, if payers only study subgroups for 

whom the treatment is of low value, they may 

not fund treatments that are of high value to 

some subgroups but of low value to others.

Different groups of patients, people with 

disabilities, or people with chronic illness may 

have dramatically 

different medication 

responses. QALYs often 

rely on research that 

does not adequately 

account for the ways in 

which many people—

especially, though 

not exclusively, those 

with rare conditions—

may have medication 

responses that vary dramatically from the 

average, either in terms of medication efficacy or 

side effects. This can create serious challenges 

under QALY-based systems, since a QALY 

calculation may result in a particular medication 

36 National Council on Disability
being deemed cost-ineffective based on the 

average patient response, whereas for patients 

within a particular subgroup or who have atypical 

medication responses, it is the only medication 

that works or the only one that provides 

outcomes without terrible side effects.

Accounting for Clinical Knowledge Not 

Reflected in the Research Literature

For individuals with rare conditions or who come 

from groups underrepresented in research, like 

people with disabilities and people of color, the 

inability of QALYs to account for information that 

primarily exists within clinical knowledge but 

has not yet made it into the research literature 

constitutes a serious problem. Many rare 

conditions do not have an adequate research 

literature to account for different subgroups 

or variation between patients in medication 

response. Since it can be difficult to study 

small populations, such knowledge may 

only exist on the part of the relatively small 

number of clinicians who specialize in treating 

such patients.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 37
38 National Council on Disability
Chapter 2: Bioethics and Quality-Adjusted Life Years

T

here have been ethical objections to use 

of QALYs nearly since they were first 

invented. There are three primary ethical 

objections: (1) that disability may not actually 

reduce quality of life; (2) that QALYs discriminate 

against people with disabilities; (3) that QALYs fail 

to account for differences between what patients 

with the same condition value.

Does Disability Reduce Quality 

of Life?

Some stakeholders, but especially bioethicists 

and people with disabilities, have argued that 

QALYs are built on a 

faulty premise: that 

life with a disability is 

inherently worse than 

life without a disability. 

As established in the 

section “Calculation of 

Quality- Adjusted Life 

Years,” QALYs work 

by lowering the value of the life-extending 

properties of treatment (or the number of years 

the individuals being treated would normally 

have left to live) by the degree to which an 

illness or disability negatively impacts quality of 

life.73 While QALYs are theoretically determining 

the “worth” of living in specific health states

and not with specific disabilities (and from this, 

the value of treatments that extend life or affect 

these health states), the reality is that people 

with specific disabilities have characteristics that 

match up with these health states. Being unable 

to walk, for example, is a core characteristic 

of paraplegia.

As described earlier in this report, QALYs 

typically evaluate the worth of a life with a 

disability based on the preferences of people 

from the general healthy population, most 

of whom do not have disabilities.74 Disability 

rights advocates are rightly concerned that 

these preferences are not based on an accurate 

understanding of what it 

is like to have a disability, 

but on stereotypes and 

a lack of understanding 

about disabilities. While 

some bioethicists believe 

that this can be mitigated 

by providing the general 

healthy population with 

information about the conditions to help inform 

their responses, others see this as flawed, such 

as Dr. David Wasserman, bioethicist at NIH, who 

told NCD that there is a great deal of evidence 

that most of the general public and the medical 

profession in particular, overestimate the badness 

of being in various health conditions that are 

classified as disability.75

Some stakeholders, but especially 

bioethicists and people with 

disabilities, have argued that QALYs 

are built on a faulty premise: that 

life with a disability is inherently 

worse than life without a disability

Quality-Adjusted Life Years and the Devaluation of Life with Disability 39
Legal scholars Wendy Hensel and Leslie Wolf 

state that

quality of life considerations are not neutral, 

even when couched in mathematical terms, 

and are very likely to 

be driven by prejudices 

and stereotypes 

concerning the 

desirability of life 

with disabilities. . . . 

By favoring those 

with no functional 

impairments, the 

protocols implicitly endorse the belief that 

the lives of individuals without disabilities 

are more valuable than that of their 

unfortunate counterparts.76

Although surveyors continue to rely on the 

healthy community’s preferences for various health 

states, it is well known that this will skew the 

results of QALY analysis. The general population 

consistently rates life with a disability much more 

negatively than people with disabilities themselves 

do. In a study with more than 2,044 participants 

from the general US population, 47 percent of all 

participants rated 

blindness as “the worst 

health condition that 

might befall them.”77 They 

ranked blindness as worse 

than AIDS, heart disease, 

the loss of a limb, and 

arthritis.78 Bioethicist Sean 

Sinclair, citing a UK study of more than 

1,000 people, said that in this study 24 percent of 

those studied said needing to use a wheelchair for 

the rest of their life would be worse than death.

79

“By favoring those with no functional 

impairments, the protocols implicitly 

endorse the belief that the lives of 

individuals without disabilities are 

more valuable than that of their 

unfortunate counterparts.

People with disabilities, however, 

consistently report that they get 

approximately the same degree 

of satisfaction from their lives as 

people without disabilities

People with disabilities, however, consistently 

report that they get approximately the same 

degree of satisfaction from their lives as people 

without disabilities. One study reported that 

patients with “locked-in syndrome”—a disability 

in which individuals are 

unable to move part or 

all of their bodies—selfreport having a similar 

quality of life to people 

without disabilities.80

An older 1979 study 

found that blind people, 

contrary to the beliefs 

of the general population, were about as happy 

or slightly happier than people who could see.81

Gallaudet professors Dirksen Bauman and Joseph 

Murray have written that Deafness should be 

reframed from “hearing loss” to “Deaf Gain,” 

in recognition of the ways in which Deaf people 

contribute to human diversity.82

Does the Use of QALYs Discriminate 

Against People with Disabilities?

The use of QALYs may lead to the devaluing of 

treatments that extend the lives of people with 

disabilities. One of the earliest and most wellknown explanations of 

this problem was by 

Harris, who articulated 

his concerns in a 1987 

journal article.83 Harris 

argued that the use 

of QALYs would lead 

to a situation in which 

funding treatments that extended the lives of 

people who could be restored to perfect health 

would be valued over treatments that extended 

the lives of people who could not be restored to 

40 National Council on Disability
perfect health, such as people with disabilities 

and chronic illnesses.84 Harris argued that it 

was morally unjust for QALYs to lead to the 

prioritization of the former over the latter.85 Harris 

said we should adopt policies that “do not violate 

the individual’s entitlement to be treated as the 

equal of any other individual in the society.”86

Disability rights advocates and people 

with disabilities oppose the use of QALYs for 

similar reasons.87 Disability rights advocates are 

concerned that the widespread use of QALYs 

by health insurance companies and healthcare 

agencies will deny people with disabilities access 

to the care that they need.88 Disability rights 

advocate Ari Ne’eman explained that such denials 

of care have in fact already happened to people 

with disabilities in countries that use QALYs 

more regularly. For example, as described in 

more detail in Chapter 3, the United Kingdom’s 

NICE determines which drugs Britain’s national 

health insurance program will cover by using 

QALYs. NICE recently denied coverage of three 

“groundbreaking” drugs for extremely rare and 

debilitating conditions.89

Ne’eman’s article states:

All three drugs work by slowing irreversible 

organ damage and cell death. While they 

can and do improve current symptoms, 

their greatest promise is in halting or 

delaying disease progression. . . . Specialty 

drugs may still be able to add years to these 

patients’ lives, but NICE and other QALYbased systems discount the value of each 

of these years [because they are years lived 

with a disability.]90

Proponents of QALYs argue that such a 

discount is irrelevant. They argue that QALYs are 

not used to decide whether to treat individual 

patients,91 but, instead, to decide which 

treatments payers will fund.92 Bioethicist Greg 

Bognar states that if a treatment or drug is costeffective, it will likely be covered. If it is covered, 

it will be offered to “all patients who need it, 

regardless of their other characteristics,” such 

as disability or race.93 Some ethicists argue that 

in fact, if people with disabilities are assessed 

as having a low quality of life, a treatment that 

dramatically improved the types of quality of 

life measured by QALYS would probably be 

considered very cost-effective.94

Additionally, they argue that the number of 

QALYs a person starts with before treatment 

does not matter. While people with disabilities 

seeking treatment for a disability will have 

lower “baseline” QALYs than a person without 

a disability, QALYs are primarily designed to 

determine the degree to which the treatment 

improves their health. Dr. Pearson provided an 

example during his interview which illustrates 

this point:

So, let’s say that you’re very sick and your 

quality of life is 0.3, and we have two 

treatments. We have a standard treatment, 

[which] improves the quality of life to 0.4 

and we have one that raised quality of 

life . . . to 0.5. We’re trying to figure out 

which is most cost-effective. Now [next], 

I’ve got two other treatments for people 

that are going to start off at 0.8, which is 

pretty good. I’ve got the same two drug 

treatments—one makes you better by 

0.1 and one makes you better by 0.2. 

The cost-effectiveness calculation is going 

to be exactly the same for those two 

comparisons among people that are very 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 41
sick, and the other among people that are 

pretty healthy. It’s a comparison of how 

much better one is versus the other. . . . 

It doesn’t matter where you start.

However, these arguments do not actually 

resolve the main concerns of QALY opponents 

such as Ne’eman—which is that use of QALYs 

may have the effect of devaluing treatments 

primarily designed for a population of people with 

a chronic illness or disability, in practice. If the 

primary purpose of QALYs is to allow decision 

makers to determine how best to spend money 

on health care, which proponents of QALYs 

do not dispute, then almost necessarily these 

decision makers are comparing unlike treatments 

and deciding which of these to fund. As 

established in Example 1 

about Connie and Bill, 

patients with chronic 

illnesses and disabilities 

who retain their disability 

after treatment do not just start with fewer 

QALYs than people who can be restored to 

perfect health—they also gain fewer QALYs from 

treatment than people who can be restored 

to perfect health. As noted in the section 

“Methodological Flaws of Quality- Adjusted Life 

Years” and earlier in this section, there are likely 

many classes of both treatments, drugs, and the 

patients they serve where this is the case. Use of 

QALYs will therefore prioritize treatments like the 

one for Bill rather than treatments like the one for 

Connie, even if what is measured is how many 

QALYs both would gain from treatment.

Health insurers are also not merely choosing 

between treatments within conditions, although 

some proponents of QALYs claim as much. 

Researchers and health economists have 

“That’s like saying that drugs for 

cystic fibrosis are also unavailable 

to patients without cystic fibrosis.

repeatedly stated that the primary purpose of 

QALYs is to allow decision makers to compare 

the cost-effectiveness of treatments for unrelated 

conditions.95

Further, use of QALYs would not be necessary 

if health insurers were comparing the costper-QALY or QALYs gained from only related 

treatments. Chapter 5, “Alternatives to the Use 

of QALYs,” describes other ways that payers 

may compare the cost-effectiveness of different 

treatments for the same condition without the 

use of QALYs. It is unlikely, after the passage of 

the Affordable Care Act, that payers in the United 

States would refuse to cover an entire class of 

patients, and QALYs would not act as justification 

for doing so. However, even if a payer treats all 

classes of patients, the quality of some classes 

of patients’ care may be 

worse, or their options 

more limited, because 

some of the potential 

treatments available 

to them were not deemed cost-effective and 

therefore not covered by their insurance due to 

the impact of their disability on QALY calculations.

Harris had an additional objection that is 

also of significance. In the real world, payers 

rarely face a choice between treating two 

disabilities of equal severity. Instead, payers 

more often face a choice akin to providing a 

little bit of quality of life to many people versus 

saving one person’s life. For example, a health 

insurance provider with a limited amount of 

money may have to choose between funding 

hip replacement surgery for many people, and 

funding a high-cost treatment that saves the lives 

of only a few people with a rare disease. QALYs 

do not distinguish between the two types of 

treatment.96 If funding hip replacement surgery 

42 National Council on Disability
for a hundred people obtains more QALYs than 

funding the high-cost treatment, then funding 

the hip replacement surgery will more than likely 

be given higher priority, even if the high-cost 

treatment saves lives. As Harris points out, this 

is quite inconsistent with the moral intuitions of 

many people.97

More significant ethical problems exist when 

the only class of drugs known to be effective for 

a certain group of patients with disabilities is not 

covered because the drugs are not considered 

cost-effective.98 In that situation, it does not 

matter that QALYs are theoretically meant to be 

used to evaluate treatments rather than patients. 

As Ne’eman wryly stated: “That’s like saying 

that drugs for cystic fibrosis are also unavailable 

to patients without cystic fibrosis.” Chapter 3 

provides specific examples of situations in which 

just such a problem has happened in other 

countries.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 43
44 National Council on Disability
Chapter 3: Utilization of QALYs in the United States

Introduction

QALYs have a complicated history of use 

in the United States. Although QALYs 

are frequently used in research, their 

use to determine benefits and coverage has 

historically been more limited compared to their 

use for this purpose in other countries. There are 

likely multiple reasons for this; some health 

economists attribute it to the United States’ 

cultural aversion to 

metrics that may 

discriminate, or the 

United States’ multi-tier, 

complex healthcare 

system.99 To understand 

this complex usage 

history, NCD undertook a 

comprehensive review of 

how QALYs are used in the United States.

Use of QALYs by the US Federal 

and State Governments

There is no one, singular policy on the use 

of QALYs across the entirety of the US 

government. Each federal agency has a distinct 

and separate policy, although the overall use 

of QALYs has followed a pattern over time. 

QALYs grew in popularity as a measure 

of cost-effectiveness during the 1990s to 

2000s, declined in popularity due to failed 

implementations of the metric during that 

time and the passage of the Affordable Care 

Act, and have recently increased in prominence 

and popularity due to concerns about rising 

healthcare costs in the United States.

One of the most prominent attempts to 

utilize QALYs in a state-run health insurance 

program was found to violate the Americans 

with Disabilities Act (ADA). Starting in 1989 

and continuing into 

the early 1990s, 

the state of Oregon 

attempted to reform 

its Medicaid program 

by ranking treatments 

in terms of their costeffectiveness.100 Oregon 

created a list of more than 700 paired treatments 

and diagnoses (an example of a paired treatment 

and diagnosis on the first list was “Diagnosis: 

mental disorders with no effective treatment; 

Treatment: evaluation”) and decided it would 

cover the 587 most cost-effective items on the 

list.101 Oregon ranked these pairs according to 

13 criteria.102 Oregon used QALYs in order to 

measure some of these criteria, particularly 

quality of life and life expectancy.103

The use of QALYs produced counterintuitive 

results: capping teeth was ranked above 

One of the most prominent attempts 

to utilize QALYs in a state-run 

health insurance program was 

found to violate the Americans 

with Disabilities Act (ADA)

Quality-Adjusted Life Years and the Devaluation of Life with Disability 45
appendectomy as it produced more QALYs for 

more people in the aggregate, even though 

an appendectomy saves a life.104 The Bush 

administration ultimately rejected Oregon’s 

Medicaid plan, as it 

was found to violate 

the Americans with 

Disabilities Act.105 A Bush 

administration official 

stated in a letter to the 

editor sent to the New 

York Times that the plan 

was rejected because 

it “in substantial part 

values the life of a person with a disability less 

than the life of a person without a disability.”106

Oregon’s Medicaid program has continued to 

ration care according to cost-effectiveness, 

however.107

From the 1990s to the late 2000s, different 

Federal Government agencies considered how 

(and where) the Federal Government should 

utilize cost-effectiveness research. Each of these 

agencies came to 

different conclusions 

about use of QALYs. For 

instance, in 2007 the 

Congressional Budget 

Office (CBO) expressed 

concerns about QALYs in 

a paper titled Research 

on the Comparative 

Effectiveness of Medical 

Treatments: Issues and 

Options for an Expanded 

Federal Role.108 In the paper, the CBO argues that 

the United States should take more of a role with 

respect to promoting the use of comparative 

effectiveness research.109 One of the ways the 

A Bush administration official stated 

in a letter to the editor sent to the 

New York Times that the plan was 

rejected because it “in substantial 

part values the life of a person with 

a disability less than the life of a 

person without a disability.

The trend toward QALY usage 

changed with the passage of the 

Affordable Care Act in 2010. Certain

federal agencies, particularly healthrelated agencies, were prohibited or 

severely limited in how they could 

utilize QALYs by the Affordable 

Care Act

CBO proposes doing this is by creating a new 

federal entity that commissions, performs, and 

evaluates comparative effectiveness research and 

how it relates to policy.110 The paper evaluates 

cost-effectiveness in this 

context. It notes that the 

use of “common metrics 

like QALYs” may “raise 

concerns among 

patients” and other 

stakeholders.111

In 2006 the 

Department of Health 

and Human Services 

evaluated the cost-effectiveness of one of its 

population-wide vaccination programs using 

“years of healthy life saved,” a direct reference 

to the use of QALYs.112 The US Public Health 

Service’s “Healthy People Initiative,” which 

measured progress toward US public health 

goals, in 2006 used QALYs “as one of its key 

metrics.”113 Throughout the late 1990s and the 

early and mid-2000s the US Food and Drug 

Administration (FDA) 

utilized QALYs as part of 

its agency rulemakings.114

The trend toward 

QALY usage changed 

with the passage of the 

Affordable Care Act in 

2010. Certain federal 

agencies, particularly 

health-related agencies, 

were prohibited or 

severely limited in how 

they could utilize QALYs by the Affordable Care 

Act. 42 U.S. Code § 1320e-1(e), which came from 

the Affordable Care Act, prohibits the Patient 

Centered Outcomes Research Institute (PCORI) 

46 National Council on Disability
from using QALYs or any other similar measure 

that “discounts the value of a life because of an 

individual’s disability,” as a “threshold” for 

determining what type of health care is costeffective.115 It also prohibits PCORI from using 

QALYs when developing healthcare coverage, 

incentives, or reimbursement programs.116

Medicare is similarly prohibited from utilizing 

“cost-effectiveness research” (a much more 

general term that applies to more than just 

QALYs) in a manner that treats “extending the 

life” of an elderly, ill, or disabled person as of less 

value than “extending the life” of someone who 

is none of the above.117

Medicare can use cost-effectiveness research 

if it is instead used for 

“determining coverage, 

reimbursement, or 

incentive programs 

under subchapter XVIII 

based upon a comparison of the difference 

in the effectiveness of alternative treatments 

in extending an individual’s life due to the 

individual’s age, disability, or terminal illness.”118

This may mean that Medicare can use costeffectiveness research to compare related 

treatments to one another, such as two different 

treatments that extend the life of someone 

with cystic fibrosis, and consider how disability 

impacts the degree to which these treatments 

extend life. However, the exact meaning of the 

phrase is ambiguous.119

The use of QALYs among federal agencies has 

increased in recent years. Dr. David Wasserman, 

at the National Institute of Health’s Department 

of Bioethics, said that “use of QALYS has 

modestly increased in the face of opposition. It 

is used by at least one US agency . . . Some sort 

of cost-effectiveness analysis is commended 

QALYs are rarely explicitly used by 

health insurers in the United States

to various agencies. I could say that there is 

a general trend toward quantifying outcomes. 

There’s a related overlapping trend to use patient 

reported outcome measures for quality of care 

assessments, which may appeal to a broader 

constituency and patient advocacy groups.”120

The Department of Veterans Affairs (VA)’s 

PBM Services office utilizes the HTA reports 

produced by ICER (described in the Introduction 

and Chapter 1) to aid the development of its drug 

formularies, which generally means the lists of 

drugs that a health insurer will cover, although 

sometimes a health insurer will cover a drug 

not listed on its formulary.121 ICER’s reports, 

as stated, utilize QALYs. The VA’s formulary 

development process 

is well-developed, 

extensive, and utilizes 

many forms of data other 

than ICER’s reports.122

The VA does not utilize a cost-effectiveness 

threshold.123

Use of QALYs by Private Health 

Insurers

Limited information is publicly available on the 

degree to which private insurance companies 

utilize QALYs to make benefits and coverage 

decisions. According to most scholarly sources, 

QALYs are rarely explicitly used by health insurers 

in the United States. Louis P. Garrison reported in 

his 2016 article that US private payers, with a few 

limited exceptions, rarely explicitly used costutility analyses (CUAs), the cost-effectiveness 

studies that rely on QALYs, in their benefits and 

reimbursement decisions.124 He stated that it was 

a “puzzle” that the United States had so many 

competent health economists who made so 

many CUAs, but that US private and public payers 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 47
rarely made direct use of their material.125 Health 

economist Peter Neumann has said in multiple126

articles127 that QALYs are rarely used explicitly 

for benefits and coverage decisions in the 

United States.

For many health insurers, use of QALYs 

or QALY-based valuations may instead be 

implicit, and part of an internal decision-making 

process over which there is little transparency 

or oversight. Eleanor Perfetto, Executive Vice 

President of Strategic Initiatives for the National 

Health Council, an organization which developed 

a Patient-Centered Value Model Rubric that is 

used to evaluate the patient-centeredness of 

value frameworks,128 said at the September 

2018 NCD stakeholder 

convening:

There’s not much 

documentation . . . 

They may or may not 

have used QALYs. We 

don’t know. But if they 

did . . . [use] them in 

their decision making, 

it probably isn’t well documented . . . And 

even if it is, it’s not public information. . . . or 

[they’ve] been used in terms of publications 

that might come out that people might put 

in journal articles, [such cost-effectiveness 

studies by researchers], for others [such as 

health insurers] to use or to consider in their 

decision making.

One important interview supported a similar 

conclusion. In Spring 2016, the International 

Society for Pharmacoeconomics and Outcomes 

Research (ISPOR) produced a Special Task 

Force Report on US value frameworks. As part 

For many health insurers, use of 

QALYs or QALY-based valuations 

may instead be implicit, and part 

of an internal decision-making 

process over which there is little 

transparency or oversight

of its research, ISPOR interviewed members 

of key stakeholder groups, including Brian 

Solow and Edmund J. Pezalla, who are PBM 

representatives.129 Solow and Pezalla were asked 

questions on the extent to which insurance 

agencies utilized cost-effectiveness research and 

value frameworks in decision making. Solow 

reported that “maybe they do,” but that with the 

exception of a few small plans, “nobody has a 

clinical policy that says we’re constructing this 

on cost-effectiveness grounds.”130 This appears 

to mean that, while cost-effectiveness is used, 

there is no explicit written policy that would 

require insurers to make decisions based on 

cost-effectiveness.

Solow and Pezalla 

were also asked to what 

extent payers used 

the value frameworks 

ISPOR investigated in 

its report. Solow and 

Pezalla reported that 

“everybody” read ICER’s 

reports, which rely on 

QALYs.131 However, 

Solow and Pezalla also reported that payers 

rarely followed the recommendations made in 

ICER’s reports “to the letter.”132 According to the 

two managers, many plans do not rely on QALYrelated aspects of these value frameworks, and 

instead attempt to do “the economic calculation 

without the QALY,” while taking the clinical and 

economic evidence ICER used to generate 

QALYs or the cost-per-QALY into account.133

Several of the individuals that NCD 

researchers interviewed did not agree with 

these statements. These individuals felt that 

private health insurers’ interest in QALYs had 

been steadily increasing over the last few years. 

48 National Council on Disability
Sara van Geertruyden of the Partnership to 

Improve Patient Care said that use of QALYs 

was “increasing” and that CVS Caremark’s 

announcement in 2018 of their intent to base 

their benefits and coverage decisions on 

ICER’s QALY-based reports134 indicates that 

“private plans and pharmacy benefit managers 

are referencing QALY-based reports [such as 

ICER’s] and using them to inform coverage 

and formularies.” Ne’eman similarly stated135

that, while QALYs have been used in academic 

contexts for some time, that they have had 

“increased utilization” in recent years in the 

benefits and reimbursement context by PBMs, 

citing the recent proposal from CVS Caremark to 

adopt a QALY threshold.

Van Geertruyden referenced a specific 

situation in which consideration of QALYs 

by health insurers had a specific impact on a 

population of patients in the United States. 

The incident involved two anti-cholesterol 

drugs, Praulent and Repatha, which target a 

protein known as PCSK9.136 As van Geertruyden 

explained, “Certain patients with genetic, familial 

high cholesterol (FH) and some other patients 

don’t respond well to statins [commonplace 

drugs that reduce high cholesterol]. PCSK9s are 

designed for this population.”137

Unfortunately, the first clinical study available 

on a PCSK9 (Repatha) was of a general 

population who were at relatively low risk for 

heart attack and stroke, rather than the patients 

with high cholesterol that the drug was actually 

intended to treat.138 Consequently, some of 

the benefits of the drug (such as prevention 

of deaths) appeared lower than they actually 

were.139 An initially high cost-per-QALY for these 

two medications was reported by ICER and, 

partially as a result of that report, according to 

van Geertruyden, as well as the higher initial cost 

of the drug, countless patients who did need the 

drug were denied it.140

The evidence presented neither indicates that 

QALYs are a controlling variable for all health 

insurance decisions in the US nor that QALYs 

are not used by health insurers at all. While few 

health insurance agencies explicitly mention costeffectiveness as the basis for their decisions, 

QALYs and the cost-effectiveness research they 

support are most likely important evidence that 

supports and guides, rather than mandates, 

various courses of action that private health 

insurers could take.

Ethical Concerns with Respect to the 

Use of QALYs in the United Kingdom 

and Their Relationship to Concerns 

in the United States

The concerns of disability rights advocates, 

bioethicists, and patient rights groups in the 

United States who oppose widespread use of 

QALYs are informed by their use in countries 

where QALYs play a much more significant role 

in healthcare decision making. QALYs are a key 

metric used by the United Kingdom’s NICE.141

The primary purpose of NICE is to decide 

which drugs and treatments will be funded by 

Britain and Wales’ national healthcare system, 

the NHS.142 To do this, NICE analyzes how 

cost-effective each new drug or treatment is 

by calculating the treatment’s cost per qualityadjusted life year.143 NICE publicly publishes its 

analyses of each new drug or treatment, which 

it refers to as “health technology appraisals” or 

“guidance.”144

NICE’s reports are known to reduce patients’ 

access to care. This is particularly likely to happen 

to patients who have a complex condition which 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 49
may require intensive, expensive treatment in 

order to manage it—which describes many 

people with disabilities.145 For example, NHS 

patients lack unrestricted access to most cancer 

drugs. According to a 2018 Avalere Health study 

of over 329 HTAs of cancer drugs created by 

governmental agencies between 2013 and 2017, 

NICE recommended access restrictions for nearly 

70 percent of the cancer drugs it assessed, and it 

rejected 22 percent of the cancer drugs.146 By 

contrast, in the United States, cancer patients 

gain access to cutting-edge medications earlier 

and are diagnosed earlier147 than in the United 

Kingdom. For some 

cancers (such as lung 

cancer) US patients have 

a higher survival rate than 

UK patients, which is 

related to their quicker 

access to diagnosis and 

medication.148

Alzheimer’s Disease

One prominent example 

of how NICE’s QALYreliant reports can have 

a negative impact on patients was its 2005 

rejection of the drugs donepezil, galantamine, 

rivastigmine and memantine for use by 

patients with mild to moderate Alzheimer’s 

Disease.149 Alzheimer’s Disease is a progressive 

neurological disease that, over time, reduces 

and eventually eliminates the affected person’s 

ability to learn and remember new information.150

The four drugs are standard treatments for 

Alzheimer’s Disease, and mainly maintain rather 

than improve the affected person’s functioning.151

According to patients with the disease and 

their families, they significantly benefit from 

NICE recommended access 

restrictions for nearly 70 percent of 

the cancer drugs it assessed, and 

it rejected 22 percent of the cancer 

drugs. By contrast, in the United

States, cancer patients gain access 

to cutting-edge medications earlier 

and are diagnosed earlier than in 

the United Kingdom

maintaining their functioning at earlier stages of 

the disease.152

NICE’s draft recommendations nonetheless 

found that the drugs were not cost-effective 

despite evidence of this benefit to patients.153

Notably, the drug donepezil (Aricept) only cost 

2.50 pounds per day per patient in 2007, only 

2 years after the draft guidance was released, 

which at the time was around the price of a 

cup of coffee.154

NICE’s recommendations were widely 

criticized by patients and other prominent 

stakeholders in the United Kingdom.155 Several 

criticisms focused on 

the validity of QALY 

calculations used by 

NICE. The Royal College 

of Psychiatrists, for 

example, argued that it 

made no clinical sense 

to deny patients with 

mild and moderate forms 

of the disease access 

to the medications, as 

these would be the very 

patients who would 

obtain a greater benefit from retaining a higher 

level of functioning for longer.156

Some researchers and doctors argued that 

using a quality-of-life focused measure was 

improper given that it is difficult to estimate 

health-related quality of life in patients with a 

progressive neurological disorder.157 It is difficult 

to translate the small but important cognitive or 

behavioral gains from these drugs into evidence 

of clinical efficacy in controlled conditions.158

Most evaluations of the quality of life of patients 

with Alzheimer’s Disease were based on the 

responses of doctors or caregivers, and it was 

50 National Council on Disability
known that the use of different proxies produced 

different results, bringing the validity of the utility 

values into question. Additionally, some 

individuals have argued that NICE’s 

recommendations were based on limited 

empirical data that, where it did exist, was 

entirely invalid when applied to some categories 

of patients. NICE’s 2005 recommendations were 

based primarily on a US study of Alzheimer’s 

Disease patients who took a specific cognitive 

functioning test known as the Mini Mental State 

Exam (MMSE), which the Royal College of 

Psychiatrists in the United Kingdom argued was 

highly influenced by age, 

sex, and English 

proficiency and was 

invalid for patients with 

intellectual and 

developmental 

disabilities.159

These heavy 

criticisms prompted NICE 

to revise its guidelines 

in 2006, which still 

restricted access,160 and 

led to significant legal 

challenges by trade 

associations and the pharmaceutical industry.161

These efforts failed,162 and patients with mild 

Alzheimer’s Disease in the United Kingdom 

were unable to obtain the drugs until 2010, 

when NICE again changed its guidelines, likely 

due to a committed campaign by patients and 

patient rights organizations.163 Currently, NICE 

recommends the use of the first three drugs for 

all patients and the last drug for patients with 

severe Alzheimer’s Disease.164

To a certain extent, the limitations NICE 

imposes on patient access to care in England and 

A UK reporter argued that the 

United Kingdom has no choice but 

to limit patient access to high-cost 

treatments, even if it means utilizing 

metrics such as QALYs, because 

paying for high-cost drugs depletes 

the NHS’s funds and therefore its 

capacity to serve many more people 

than the few who benefit from a 

high-cost treatment

Wales are mainly due to the United Kingdom’s 

national healthcare system. The NHS has a 

limited budget and yet must provide care to all 

citizens. The issue of how to allocate scarce 

funds is therefore particularly pressing. A UK 

reporter argued that the United Kingdom has no 

choice but to limit patient access to high-cost 

treatments, even if it means utilizing metrics 

such as QALYs, because paying for high-cost 

drugs depletes the NHS’s funds and therefore 

its capacity to serve many more people than the 

few who benefit from a high-cost treatment.165

However, similar problems exist in the US’s 

national healthcare 

programs, which must 

provide a basic level of 

care to everyone who 

is eligible. While this 

type of rationing may be 

inevitable in healthcare, 

it nonetheless poses an 

existential threat to many 

people with disabilities. 

Crucially, there may be 

alternatives to the use 

of the quality-adjusted 

life year. For more 

information on the alternatives that have been 

proposed, see Chapter 5, “Alternatives to the Use 

of QALYs.”

Cystic Fibrosis

NICE’s treatment of the cystic fibrosis drug 

Orkambi (lumacaftor/ivacaftor) illustrates the risks 

QALYs pose to people with rare and complex 

conditions even when the cost-effectiveness 

assessment does not assign patients a markedly 

reduced health utility value. Cystic fibrosis is a 

genetic disease which causes thickened mucus 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 51
secretions to progressively block the lungs and 

digestive system.166 Eventually, most people with 

CF will die from respiratory failure.167 In 2017, the 

median age of death for patients with CF in the 

UK was 31 years.168

Until recently, only treatments for the 

symptoms of CF existed. Nebulized medications 

such as Pulmozyme and hypertonic saline thin 

mucus so it is easier to clear, but do not correct 

the defect leading to the production of thickened 

mucus.169 Orkambi, manufactured by Vertex 

Pharmaceuticals, is a member of a new class 

of drugs known as CFTR modulators.170 These 

drugs partially restore correct production and 

function of the protein that is defective in cystic 

fibrosis.171 Each CFTR modulator is only clinically 

appropriate for a subset of CF patients with 

specific mutations.172

In July 2015, the FDA approved Orkambi for 

patients 12 years and older with homozygous 

F508del mutations.173 About half of CF patients 

in both the United States and the United 

Kingdom have this genotype. NICE issued an 

initial rejection in mid-2016, estimating the 

drug’s incremental cost-effectiveness ratio to 

be between £218,248 to £349,337 per QALY 

(approximately $280,000 to $460,000 per year; 

the lower value relies on the assumption that 

after 10 years, prices would be reduced by the 

introduction of a generic).174 NICE’s officially 

recommended cost-effectiveness threshold 

window is far below this, ranging from £20,000 

to £30,000 per QALY.175

The detailed justification of NICE’s costeffectiveness assessment illustrates the 

problems with attempting to capture treatment 

benefits perceived by people with disabilities 

using general population measures. Though 

many adults with CF have significant functional 

limitations and may spend weeks per year in 

the hospital or on home IV treatments, patients 

often give high ratings on general quality of life 

(QoL) scales.176 Patients in Vertex’s study gave 

baseline health-related QoL ratings on NICE’s 

preferred instrument that corresponded to a 

median health utility value of 1, equivalent to the 

healthy, nondisabled population.177 This left no 

room for subjective improvement in quality of life. 

The NICE appraisal states that “both the clinical 

and patient expert explained [to the committee] 

that people with cystic fibrosis may perceive their 

health-related quality of life to be equivalent to 

that of people without cystic fibrosis because 

they have never known any other health state.”178

However, the committee “understood from 

the clinical experts that they considered that 

the 5 dimensions of the EQ-5D questionnaire 

generally captured most of the important effects 

of cystic fibrosis” and deemed there to be 

insufficient evidence that the general population 

measure was inappropriate.179 As a result, the 

estimated cost-per-QALY for Orkambi could only 

incorporate its predicted longevity benefit.

In the United States, ICER has also used the 

QALY to evaluate Orkambi’s cost-effectiveness.180

ICER chose to assign health utility values based 

on a measure of patients’ lung function.181 A CF 

patient’s health utility value could be at minimum 

0.625 and at maximum 0.92.182 This meant 

that the expected reduction in rate of disease 

progression could be reflected in increased 

amounts of time at higher utility values. However, 

this degree of discounting meant that ICER’s 

assessment resulted in an incremental costeffectiveness ratio of $890,700 per QALY,183

much higher than NICE’s estimate (and providing 

justification for potential denial of coverage 

by payers).

52 National Council on Disability
In both evaluations, patients are 

disadvantaged by the forced tradeoff between 

increased length and quality of life. Additionally, 

the discrepancy in methods and assessed 

treatment value make the metric’s claimed 

objectivity seriously questionable.

Three years after NICE’s initial rejection, CF 

patients still do not have access to Orkambi on 

the English NHS. In the summer of 2018, NHS 

England offered to cover all of Vertex’s existing 

and future therapies at a 90 percent reduction 

from the list price.184 This would amount to 

less than £10,000 per patient per year.185 This 

cost is less than that 

of Pulmozyme, a 

symptomatic treatment 

first approved by the US 

FDA in 1993.186 Vertex 

has refused this offer, 

stating that it would 

set a precedent for 

price negotiations in other countries that would 

make funding further research and development 

impossible.187

Use of Similar Models in United States 

National Health Insurance Programs

Disability and patient rights advocates have 

expressed concerns that, as the United States 

increasingly attempts to find ways to save money 

in healthcare contexts, it will look towards 

modeling its own national health insurance 

programs after those in the United Kingdom 

[S]trict prioritization that is overly 

reliant on QALYs, similar to the kind 

utilized in the United Kingdom, is 

contrary to US civil rights law and 

disability policy

and other countries that use QALYs. Some US 

government agencies are already investigating the 

prospect of doing so. The Centers for Medicare 

and Medicaid recently published an Advance 

Notice of Proposed Rulemaking (ANPRM) which 

proposes an International Pricing Index (IPI).188 The 

IPI would base the prices of certain drugs covered 

under Medicare Part B on reference prices from 

16 other countries. Many of these countries—for 

instance, the United Kingdom, Ireland,189 and 

Canada190—use QALYs to make benefits and 

coverage decisions and limit their healthcare 

costs. At the state level, the Drug Utilization 

Review board in New 

York voted unanimously in 

April 2018 to recommend 

that state Medicaid 

payments for Orkambi be 

reduced by 70 percent 

in order to meet 

ICER’s recommended 

maximum threshold of $150,000 per QALY. Drug 

manufacturers are unlikely to accept such extreme 

price reduction demands, posing a threat to 

treatment access for patients in states choosing 

to enforce cost-effectiveness thresholds.

The failure of Oregon’s initial waiver is 

instructive. While some consideration of costeffectiveness is reasonable in national health 

insurance programs, strict prioritization that 

is overly reliant on QALYs, similar to the kind 

utilized in the United Kingdom, is contrary to US 

civil rights law and disability policy.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 53
54 National Council on Disability
Chapter 4: Case Study: CVS Caremark

Introduction

NCD’s case study for this report 

investigates one particular upcoming 

use of the quality-adjusted life year in 

the United States: the PBM CVS Caremark’s 

recent decision, in August 2018, to allow selfinsured employers to exclude drugs from 

their formularies that were found to not be 

cost-effective, based on the cost exceeding 

a threshold of $100,000 per QALY.191 CVS 

Caremark’s decision is controversial. A wide 

variety of stakeholders have spoken on how 

CVS Caremark relates to the viability of QALYs 

as a means to cut healthcare costs and aid 

healthcare coverage decisions in the United 

States. While some stakeholders lauded the 

decision as a victory that would drive down 

costs for consumers, others were concerned 

that CVS Caremark’s use of QALYs would lead 

to blanket, one-size-fits-all coverage decisions 

that would prevent people with disabilities from 

accessing the medications and treatments that 

they need.

Background

CVS Caremark is a type of company known as 

a pharmacy benefit manager, or PBM. PBMs 

contract with health insurers and employer 

sponsors of health insurance plans and act 

as administrators of their prescription drug 

benefits.192 Their clients are diverse, and can be 

private health insurance companies, employer 

sponsors of employee health insurance plans, 

and state Medicare and Medicaid agencies, 

among others.193 While PBMs began largely as 

“middlemen” who processed health insurance 

claims, they now have many other important 

roles in the health insurance industry.194 Modernday PBMs can: (1) help determine which drugs 

will be covered by aiding in the development 

of drug formularies; (2) make reimbursement 

decisions, deciding how much pharmacies in 

their client’s network will be reimbursed for 

their services; and (3) operate pharmacies 

themselves.195

PBMs, given that they manage the prescription 

drug benefits of more than 266 million Americans 

according to the Pharmaceutical Care 

Management Association,196 have significant 

influence over what drugs are and are not 

covered by health insurance. According to 

Ne’eman, PBMs are, from the insured person’s 

perspective, “payers themselves.”197 CVS 

Caremark is a particularly large PBM. CVS 

Caremark, along with two other PBMs, Express 

Scripts and OptumRx, administer 70 percent of 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 55
all PBM-managed prescription drug claims in the 

United States.198 Any action CVS Caremark takes, 

therefore, has an impact on the lives of millions 

of Americans.

CVS Caremark’s Decision

In August 2018, CVS Caremark released a white 

paper titled, Current and New Approaches 

to Making Drugs More Affordable. The 

white paper described the steps that CVS 

Caremark intends to take to reduce the cost 

of prescription drugs in the United States.199

One of the steps CVS Caremark described 

in its white paper is “Reducing Launch Price 

Using Comparative 

Effectiveness.” In 

the white paper, CVS 

Caremark stated that 

parts of Europe have a 

loose cost-effectiveness 

threshold of $50,000 

per QALY, which in 

CVS Caremark’s view 

encouraged drug 

manufacturers in 

Europe to launch new 

prescription drugs at lower prices in order 

to meet this threshold.200 CVS Caremark 

stated that the US “does not have any such 

programs,” and that therefore the launch prices 

of new prescription drugs in the United States 

continues to rise.201

CVS Caremark then explained that it was 

launching a new program, which would allow 

some of the PBM’s clients to exclude from their 

drug formularies any drug with a launch price 

greater than $100,000 per QALY.202 CVS Caremark 

would use the HTAs produced by ICER to 

determine whether a drug’s launch cost-per-QALY 

PBMs, given that they manage 

the prescription drug benefits of 

more than 266 million Americans 

according to the Pharmaceutical 

Care Management Association, 

have significant influence over what 

drugs are and are not covered by 

health insurance

fell below or at the threshold.203 CVS Caremark’s 

policy is only available to self-funded insurance 

plan sponsors, who are mostly employers.204 CVS 

Caremark’s policy does not affect “breakthrough 

therapies,” which are medications that the Food 

and Drug Administration deems more effective at 

treating a “serious or life-threatening” condition 

than existing therapies.205 CVS Caremark’s theory 

was that if enough PBM clients agree to exclude 

drugs from their formularies in this manner, drug 

manufacturers will be forced to lower the launch 

prices of their drugs.206

Responses to the CVS Caremark 

Decision

CVS Caremark’s decision 

attracted controversy as 

soon as it was published, 

with both positive and 

negative responses 

written in response 

to CVS Caremark’s 

announcement.

Positive responses 

emphasized the 

significant role that 

drug manufacturers play in driving up the price 

of prescription drugs, and saw CVS Caremark’s 

policy as a “bold move” to curtail expanding 

launch prices.207 Max Nisen, a Bloomberg Opinion

columnist, stated that CVS Caremark’s policy 

was a positive change but that it “did not go far 

enough,” suggesting that CVS Caremark should 

also exclude “breakthrough therapies” as they 

were becoming more commonplace and were 

often highly expensive.208 The online magazine 

Vox, summarizing the statements of Dr. Wallid 

Gellad, stated that “Stricter formulary designs 

are one of the few direct tools that might be 

56 National Council on Disability
able to influence drug manufacturers’ behavior,” 

and Gellad said that “something like this is the 

inevitable future.”209 However, Gellad criticized 

CVS Caremark’s exclusive use of ICER’s costeffectiveness analyses, stating that “the idea 

that we base something solely on a cut point 

determined by one cost effectiveness analysis 

from ICER is a big step to take.”210 Gellad, like 

Nisen, also wondered if the new program would 

actually impact that many drugs, given that it 

would exclude high-cost “breakthrough” drugs.211

Negative responses emphasized the arbitrary 

nature of the $100,000 cost-per-QALY threshold, 

the inability of QALYs and other kinds of costeffectiveness to fully 

gauge a medication’s 

worth to patients, and 

the danger that the use 

of QALYs will greatly 

reduce access to care. 

Robert W. Dubois, of the 

National Pharmaceutical 

Council, stated that 

evaluating all medications for all conditions using 

a single $100,000-per-QALY cutoff threshold was 

“inappropriately blunt” and arbitrary. Dubois 

noted that most other entities that use costeffectiveness, including ICER itself, either use 

variable thresholds (such as between $100,000 

to $150,000 per QALY) or do not use their 

threshold as an absolute cut-off point.212 He 

stated that a singular threshold did not account 

for significant differences between how different 

patients with the same condition can respond to 

a medication.213 Two subgroups of patients with 

the same condition could receive a different 

number of QALYs, and thereby a different cost 

per QALY214 would be calculated for the drug. 

Dubois also said that CVS Caremark’s plan failed 

Ninety patient and disability 

rights organizations signed onto a 

September 2018 letter to CVS’s 

CEO, Larry Merlo, which opposed 

the policy

to account for societal benefits of a drug, such as 

reduced caregiver burden or increased 

productivity.215

Patient rights organizations shared Dubois’ 

concerns and additionally criticized CVS 

Caremark’s proposed use of the quality-adjusted 

life year itself. Tony Coelho of the Partnership 

to Improve Patient Care (PIPC) argued that 

CVS Caremark’s new policy, by relying on 

QALYs, would discriminate against people 

with disabilities and elderly people in the ways 

described in Chapter 2, “Bioethics and the 

Quality-Adjusted Life Year,”216 in that QALYs will 

undervalue treatments for people with chronic 

conditions and disabilities 

who can never be 

returned to “perfect 

health,” as defined 

by researchers using 

QALYs. Ninety patient 

and disability rights 

organizations signed 

onto a September 2018 

letter to CVS’s CEO, Larry Merlo, which opposed 

the policy.217 Disability rights advocates raised 

similar concerns, and highlighted the particularly 

negative impact of such a policy on people with 

rare diseases and conditions.218

Some news outlets primarily commented on 

the relationship between CVS Caremark’s new 

policy, the Institute for Clinical and Economic 

Review, and QALYs. Economics magazine 

Forbes, for instance, commented that 

ICER’s methodology was very similar to the 

methodology used by the United Kingdom’s NICE 

agency, and titled its article, “Will CVS Caremark 

Make ICER the American NICE?”219 ICER has 

defended its use of QALYs in response to the 

widespread criticisms of the metric by patients 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 57
and disability rights groups. An ICER 

representative stated the following:

QALY is recognized as the gold standard for 

measuring how much a treatment improves 

patient lives, and it effectively rewards 

innovative medicines that significantly 

improve the lives of patients most in need. 

Patient populations that start off with a 

lower quality of life—whether because 

of a serious chronic illness or disability—

actually represent the greatest opportunity 

for treatments to achieve a significant 

improvement in QALYs.220

CVS Caremark’s Response to 

Criticisms and Stakeholder Concerns

CVS Caremark’s 

initial response to the 

criticisms has been 

limited. In a HealthAffairs

blog article responding to Dubois, CVS 

representatives Troyen Brennan and Surya Singh 

explained that the cost per QALY is determined 

by both the medication’s impact on “quality of 

life” (as measured by QALYs) and the price the 

manufacturers set for the drug.221 Given this, a 

manufacturer could lower the drug’s cost-perQALY by setting a lower launch price for the 

drug.222 The article did not address concerns 

that QALYs inherently undervalue certain 

categories of patients, and describes QALYs as a 

“quantitative method” that “help[s] stakeholders 

compare the costs and effectiveness of 

medications.”223 They also do not address Dubois’ 

concern that a singular cost-per-QALY threshold 

does not account well for situations in which 

“Will CVS Caremark Make ICER the 

American NICE?”

different groups of patients respond differently to 

a medication and thereby generate different costper-QALY estimates for the same drug.224

An article by STAT News in September 

2018 reports that CVS Caremark is engaged in 

discussions with representatives of some of 

the 90 groups that signed PIPC’s September 

12th letter.225 Troyen Brennan, CVS’s Executive 

Vice President said, “It behooves us to spend 

some time to understand the concerns of the 

disability community and, if necessary, modify 

the measures so the process treats every life as 

being of equal value. We’ll go with the program 

we have now, but we’re looking for ways that we 

might modify it down the line.”226 As of the time 

the article was written, CVS Caremark’s policy 

was still set to begin in 2019.227

Conclusion

As of February 2019, 

there was no news 

available that indicates 

the impact of CVS Health’s implementation of 

its new policy. Its ultimate effect on patient 

access to prescription medications is therefore 

unknown. The discussion surrounding CVS 

Caremark’s new policy, however, brought the 

QALY into the public eye. CVS Caremark’s 

status as one of the largest pharmacy benefit 

managers in the United States meant that 

its change in policy could have an impact on 

millions of Americans, particularly Americans 

with disabilities. Central to the debates about 

CVS Caremark’s policy was its use of QALYs, 

and whether or not it can be used as a tool to 

control rising prescription drug costs without 

harming patients with chronic illnesses and 

people with disabilities. Some individuals 

58 National Council on Disability
lauded CVS Caremark’s attempt to bring down 

prescription drug costs, while others raised 

reasonable concerns about CVS Caremark’s 

use of both a bright-line cost-effectiveness 

threshold and the flawed but ubiquitous QALY. 

NCD presents this case study as an overview 

of the arguments for and against use of 

QALYs in benefits and coverage decisions, and 

recommends that the Department of Health 

and Human Services carefully consider all of the 

issues and avoid the use of QALYs or any similar 

metric in its own health programs.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 59
60 National Council on Disability
Chapter 5: Alternatives to the Use of QALYs

Various alternatives to the use of qualityadjusted life years have been proposed. These alternatives differ from one another 

in a variety of ways, including: (1) whether or not 

the alternative attempts to serve all of the same 

functions as QALYs; (2) whether the alternative 

uses the same means 

of assessing which 

treatments are most 

“valuable” as 

conventional QALYs, 

or whether it uses a 

different means of 

assessing the “value” 

of a treatment; and 

(3) whether the 

alternative has actually been used in practice, or 

whether it is only theoretical.

Equal Value of Life Years Gained 

(evLYG) Supplementary Measure

In response to criticism from disability rights 

activists regarding the QALY, in December 2018, 

ICER announced their intent to use a 

supplementary measure in addition to the QALY, 

entitled the equal value of life years gained 

(evLYG). The evLYG is intended to act as a 

supplement, rather than a replacement, for the 

QALY. It offers an additional unweighted measure 

of years of life extended utilizing particular 

treatments (without the reduction in value of a 

year of life extended created by the use of a 

health utility or disability weight), intended to 

allow an observer or payer to see if there is a 

significant discrepancy between the QALY and 

evLYG outcome. Early use of the evLYG indicates 

that there are such 

discrepancies. For 

example, in ICER’s 

analysis of Spinraza, a 

new breakthrough 

therapy for Spinal 

Muscular Atrophy with 

significant life-extension 

potential, ICER concluded 

that utilizing a $100,000 

to $150,000 per Quality-Adjusted Life Year 

(QALY) threshold, Spinraza’s maximum 

permissible reimbursement level for people 

with presymptomatic SMA would be $72,000 to 

$130,000 for the first year of treatment and 

between $36,000 to $65,000 for each successive 

year. Utilizing the evLYG at the same monetary 

threshold, the maximum permissible 

reimbursable price would be between $83,000 to 

$145,000 during the initial year and $41,00 to 

$72,000 for each successive year. Both are 

significantly below Spinraza’s cost of $750,000 for 

the initial year and $375,000 per year thereafter, 

suggesting that Spinraza would not be covered 

In response to criticism from 

disability rights activists regarding 

the QALY, in December 2018, ICER 

announced their intent to use a 

supplementary measure in addition 

to the QALY, entitled the equal value 

of life years gained (evLYG)

Quality-Adjusted Life Years and the Devaluation of Life with Disability 61
under QALY systems or systems that utilized the 

QALY and the evLYG together. (In the United 

Kingdom, Spinraza is not covered due to the 

QALY analysis conducted of the drug by NICE.)

There are other challenges to the evLYG that 

indicate that it is not a suitable alternative to the 

QALY. First, as evidenced by the assessment of 

Spinraza, denial of coverage is possible under the 

QALY/evLYG system, even where a drug would 

provide significant clinical benefit, including life 

extension. Second, the QALY/evLYG system 

still relies on health utility weights to measure 

quality of life improvements, despite the fact that 

such measures are typically derived from survey 

data and do not account for the complexity of 

the preferences and 

experiences of people 

with disabilities. Third, 

the QALY/evLYG system 

affords no opportunity 

to account for clinical 

knowledge not reflected 

in the research literature, 

a significant concern 

articulated in Chapter 1. Finally, even within the 

narrow emphasis on life extension, ICER provides 

no guidance to payers as to which reimbursement 

level to prioritize—the one derived from the QALY 

or the one derived from the evLYG.

Not Using QALYs When Determining 

Cost-Effectiveness

Payers could simply not use QALYs when 

determining the cost-effectiveness of treatments 

or drugs at all. QALYs are only one possible 

outcome measure that researchers could use 

to determine the impact of a treatment on 

extension of life and quality of life.228 Costeffectiveness studies could instead use other 

[T]hey could use a cost-benefit 

analysis, which converts the health 

outcomes resulting from treatment 

into an amount of money and then 

subtracts that amount of money 

from the cost of the treatment

measures that present fewer ethical problems, 

or simply are better at expressing the true benefit 

patients gain from treatment, than QALYs.

For example, the researcher could determine the 

number of individual cases of disease prevented, 

the number of deaths that were prevented, the 

number of years of life that were saved or 

would be saved, or any other possible benefit 

of the treatment. Payers could then evaluate 

whether this health outcome was worth the 

cost of the treatment.229 Ariel Beresniak provides 

an example where, for rheumatoid arthritis, 

if the benefit of the treatment is remission, 

the researcher could determine the “cost 

per clinical remission.”230 The use of costeffectiveness generally 

may still devalue clinically 

effective but highcost treatments (such 

as, especially, cancer 

treatments),231 which 

may harm individuals 

with disabilities and 

other chronic illnesses.

Instead of using a cost-effectiveness 

analysis, policymakers and researchers could 

also determine whether a treatment’s value 

outweighs its costs in some other way. For 

instance, they could use a cost-benefit analysis, 

which converts the health outcomes resulting 

from treatment into an amount of money and 

then subtracts that amount of money from the 

cost of the treatment.232 For example, in a costbenefit analysis, an insurer could determine how 

much money the insurer would save if a specific 

type of cancer were treated (as compared to the 

costs of hospitalization) and then subtract that 

amount of money from the cost of the cancer 

treatment.

62 National Council on Disability
There are still ethical concerns about the use 

of cost-benefit analysis in a healthcare context. 

One concern is that converting healthcare 

outcomes into money is a controversial idea that 

is often described as “putting a dollar value on 

life.” This is also similar to the idea of “cost per 

QALY,” which is also a way of putting a cost on a 

healthcare outcome and determining whether the 

cost is reasonable.233 Nonetheless, cost-benefit 

analysis is one of the more frequently used 

alternatives to cost-effectiveness analysis. 

Cost-benefit analysis is commonly used in 

non-healthcare sector contexts that still concern 

public health and wellness. For instance, the 

Environmental Protection 

Agency uses cost-benefit 

analyses when analyzing 

the impact of its 

environmental 

regulations. These 

regulations are analyzed 

primarily in terms of the 

degree to which they 

improve the health of the 

American public at 

large.234 The Environmental Protection Agency 

has experimented with the idea of using 

QALYs,235 but primarily uses cost-benefit 

analysis.236

Multi-Criteria Decision Analysis

Multi-criteria decision analysis (MCDA) is another 

alternative to QALYs that better acknowledges 

the complexity of healthcare decision-making. As 

explained by the Innovation and Value Initiative, 

MCDA allows decision-makers to simultaneously 

consider many different factors relevant to 

a healthcare decision (such as cost, clinical 

outcomes, and administrative burdens) and 

MCDA allows decision-makers 

to simultaneously consider 

many different factors relevant 

to a healthcare decision (such 

as cost, clinical outcomes, and 

administrative burdens) and 

determine how important each of 

these factors is to them

determine how important each of these factors is 

to them.237

A payer using MCDA would first rank each 

factor that is relevant to the decision against 

one another.238 For instance, the decision-maker 

would determine whether clinical outcomes 

or cost matters more to them in a healthcare 

decision. Each of the criteria would then be 

given a weighted “score” representing that 

criteria’s importance to the decision-maker. 

Normally, when MCDA is used, there are a great 

many criteria that are being ranked in order of 

importance—sometimes as many as 15.239

Next, researchers would compare how each 

of the treatments being 

considered relate to one 

another. For example, 

Treatment A might have 

better clinical outcomes, 

but Treatment B costs 

less. Researchers would 

then create a score 

representing how each 

of the treatments fare 

with respect to each 

of the criteria being considered. For example, 

Treatment A would receive a higher score for 

clinical outcomes than Treatment B, but a lower 

score for cost.

The next step is dependent on the decision 

that’s being made and the criteria that are 

being assessed, but when making a health care 

decision, it often involves generating a single 

average weighted score for each treatment that 

is the aggregate of both how the treatment 

scores on each of the criteria and how important 

those criteria are to the decision-maker, which 

then shows the relative value of the treatments 

to one another.240

Quality-Adjusted Life Years and the Devaluation of Life with Disability 63
MCDA has a variety of possible applications. 

For example, the Innovation and Value Initiative 

uses MCDA in its condition-specific model for 

rheumatoid arthritis. The model is intended to 

help a variety of different healthcare decisionmakers determine the value of different antirheumatic (that is, anti-arthritis) drugs to them.241

Importantly, the model can be altered to allow 

the decision-maker to consider how the drug will 

impact different subgroups of patients, such as 

subgroups of patients of a specific age, gender, 

severity of arthritis, etc.242 As established in the 

section “QALYs Fail to Distinguish Between 

Subgroups of Patients with the Same Condition,” 

QALYs’ limited use for these purposes is a flaw 

of QALYs. Some stakeholders, such as some 

health economists, feel that use of MCDA is the 

most promising alternative to QALYs.243

MCDA does possess a number of flaws, the 

largest of these being ease of use. Researchers 

must accurately weigh what can be a large 

number of possible criteria accurately to make 

decisions. Additionally, according to Beresniak, 

many MCDA models are more complex than 

QALYs and may require a greater degree of 

expertise in order to be used.244 However, 

given that MCDA can be used to compare 

a wide variety of health-related criteria 

simultaneously—including both life extension, 

specific clinical benefits of treatment, and 

quality of life—a form of MCDA may represent 

the most likely effective alternative to the use 

of QALYs. NCD recommends that a conditionspecific form of MCDA, with values based 

upon the perspectives of patients with the 

condition as seen in the Patient Perspective 

Value Framework, be utilized by payers to gauge 

the cost-effectiveness of treatments for the 

same condition.

Alternatives to QALYs That Use 

Primarily Patient Preferences

Patient rights groups believe that the best 

alternatives to QALYs allow patients with 

the condition being treated to define which 

treatments for the condition are of the highest 

“value,” and also what a “high-value” treatment 

is. While public and private insurers consider 

low-cost, clinically effective treatments to be 

of the highest value, patients may consider a 

wider variety of factors as important, such as 

the treatment’s impact on the ability to maintain 

relationships with one’s family and friends.245

Patient rights groups also argue that a good 

alternative to QALYs allows patients to evaluate 

the costs and benefits of a treatment across 

multiple areas of patients’ lives.

Patient Perspective Value Framework

FasterCures’ “Patient Perspective Value 

Framework” (PPVF) is a value framework that 

may satisfy PIPC’s criteria.246 While the PPVF 

has not yet been used extensively, FasterCures 

provides general examples of how the PPVF 

could be used in a number of situations, including 

by individuals as a decision-making aid and by 

public healthcare programs.247

The PPVF is divided into five broad “domains,” 

which are the five types of information patients 

usually consider when making healthcare 

decisions.248 These five domains are:

■ Domain 1: Patient Goals and Preferences,

■ Domain 2: Patient-Centered Outcomes,

■ Domain 3: Patient and Family Costs,

■ Domain 4: Quality and Applicability of 

Evidence, and

■ Domain 5: Usability and Transparency.249

64 National Council on Disability
Information from Domains 1 through 4 is 

used by the decision maker to determine how 

valuable a drug or treatment is as compared to 

another drug or treatment, or multiple drugs or 

treatments, for the same condition. Researchers 

first attempt to determine what patients with 

the condition being treated value most in a 

healthcare treatment—that is, evidence for 

Domain 1. They then gather evidence related 

to: (1) Domain 2, which represents the health 

benefits and drawbacks of each intervention or 

drug for the patient; (2) Domain 3, the financial 

costs to the patient; and (3) Domain 4, how 

high-quality and comprehensive the evidence 

of a drug or treatment’s 

clinical effectiveness 

is. Domain 5 acts as a 

“foundation” for the 

other four Domains. A 

metric must be usable 

to be useful.

Researchers then 

weight the evidence 

from Domains 2, 3, and 

4 based on the evidence 

they gathered for Domain 

1, which is evidence of 

the goals and preferences of patients with the 

condition.250 PPVF then assigns a score to each 

treatment based on these calculations. PPVF’s 

assessment method appears similar to a form of 

multicriteria decision analysis, described further 

in the “Multicriteria Decision Analysis” section, 

which specifically considers matters of import 

to patients.

The PPVF uses “patient goals and 

preferences” to evaluate a far broader array 

of information about a treatment’s impact on 

patient quality of life than whether the treatment 

The PPVF uses “patient goals 

and preferences” to evaluate a 

far broader array of information 

about a treatment’s impact on 

patient quality of life than whether 

the treatment extends life or has 

an impact on the specific, limited 

aspects of health-related quality 

of life 

extends life or has an impact on the specific, 

limited aspects of health-related quality of life 

typically measured by QALYs. For example, 

Domain 2, “Patient-Centered Outcomes,” uses 

patient preferences to evaluate the complexity of 

the treatment regimen and the treatment’s risks, 

side effects, and complications for patients.251

This is a more realistic assessment of the myriad 

possible impacts a healthcare treatment can 

have on the lives of patients. The broader array of 

quality of life considerations would also prevent 

two treatments from receiving the exact same 

score, as no two treatments would have exactly 

the same impact on every single domain.

PPVF and similar 

methods can only 

be used to compare 

two different drugs or 

treatments for the same 

condition.

252 Payers 

could not use the PPVF 

to determine whether a 

drug for cystic fibrosis 

would be of higher 

value than a drug for 

hypertension. Some 

stakeholders feel that this 

would not be a flaw at all, as it protects against 

many of the ethical issues that occur when 

QALYs are used to compare unlike treatments. 

The PPVF has never been used, however.253

It is therefore unclear how it would operate 

in practice.

The Efficiency Frontier

The German Institute for Quality and Efficiency in 

Health Care has adopted a method of assessing 

cost-effectiveness known as the efficiency 

frontier.254 Generally, an “efficiency frontier” in 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 65
66 National Council on Disability

Figure 1. Example of an efficiency frontie

Source: German Institute for Quality and Efficiency in Health Care.257

economics is the set of possible actions that 

offer either the greatest possible benefit for the 

cost involved or the lowest possible cost for the 

amount of benefit involved.255 A set of possible 

actions can be expressed as points on a scatter 

plot, and the “efficiency frontier” can be 

expressed as any of these points that line up 

with a line going through 

the center of the 

graph.256 Figure 1 is an 

example of an efficiency 

frontier.

The line going through 

the center of the graph 

is the efficiency frontier. 

The points on the graph 

represent, in the healthcare-specific example in 

Figure 1, treatments. The points along the line 

represent the most cost-effective options. While 

in an investment context, no points above the line 

could exist, in a healthcare context, they would 

represent healthcare treatments that are highly 

Generally, an “efficiency frontier” 

in economics is the set of possible 

actions that offer either the greatest 

possible benefit for the cost 

involved or the lowest possible cost 

for the amount of benefit involved

cost-effective, or much more cost-effective than 

current approaches.258

The approach Germany proposed for 

evaluating healthcare treatments is to place the 

cost per patient on the x-axis (horizontal axis) of 

the graph, and the possible benefit on the y-axis 

(vertical axis) of the graph.259 The researcher 

would then add points to 

the graph representing 

different possible 

treatments for the same 

condition, and could use 

the resulting scatterplot 

to see which of these 

treatments is most 

cost-effective—such as 

how cost-effective a new treatment would be as 

compared to current treatments.260

The graph format allows health economists to 

easily compare the costs and benefits of various 

interventions to one another. For example, in 

Figure 1, the “negative efficiency” line shows that 
the hypothetical treatment represented by the red 

point closest to the blue line is clearly more 

cost-effective than the red point farther away. 

However, Treatment A provides slightly more 

benefits but costs more than the treatment on 

the blue line beneath it, though it is less costeffective than the treatment on the line above it.

A researcher using an efficiency frontier 

could determine that the benefit of a lung cancer 

treatment was “restoring/maintaining lung 

function,” and determine a way to measure lung 

function in terms of percentages or numbers.261

The researcher could also determine how 

much each lung cancer treatment would cost 

per patient per year. The researcher would 

then graph each lung cancer treatment along 

a scatter plot where 

“restoring/maintaining 

lung function” was the 

benefit on the y-axis, and 

cost per patient per year 

was along the x-axis. The 

researcher could then 

see visually which lung cancer treatments were 

the most efficient use of resources.

The main benefit of this approach is that it is 

clear, easy to use, and transparent. Additionally, 

it does not require the health economist to use 

QALYs as the measure of a treatment’s benefit.262

The benefit on the graph could instead be the 

specific benefit that comes from the treatments, 

rather than an arbitrary number representing 

only some limited aspects of “quality of life” 

combined with the extent to which a treatment 

extends life. However, if QALYs are not used, 

it would only be possible to look at either one 

benefit of a healthcare treatment at a time, or 

different benefits that have been aggregated into 

a single number.263

Many health economists have 

remarked that one of the reasons 

QALYs persist despite their flaws is 

that there is no perfect replacement

Are There Alternatives to QALYs 

That Perform the Same Functions 

as QALYs?

QALYs continue to enjoy widespread use 

by health economists, researchers, and 

policymakers internationally and in the United 

States, despite the existence of alternatives. 

This is likely because, as multiple researchers 

have noted, QALYs are: (1) easy for policymakers 

to use (as they combine quality and quantity of 

life together and so payers would not need to 

determine how effective the drug is at improving 

quality and quantity of life separately); (2) wellestablished; and (3) allow policymakers to 

compare unrelated treatments to one another. 

As explained in the sections pertaining to each 

alternative, no one 

alternative serves all of 

the functions of QALYs.

Many health 

economists have 

remarked that one of 

the reasons QALYs 

persist despite their flaws is that there is no 

perfect replacement. These individuals have 

stated that while QALYs are imperfect at best, 

there are no sufficiently developed alternatives 

to QALYs and therefore QALYs remain “the 

best option available.”264 Other stakeholders 

disagree with this premise. Beresniak has 

argued that it is not sufficient, if QALYs lack 

scientific validity and do not measure what they 

claim to measure, to simply state that QALYs 

are the “best” option available, although he, 

too, says that no single alternative can act as a 

replacement.265

Some of the individuals NCD interviewed 

argued that no metric should serve all of the 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 67
functions of QALYs, such as comparing unrelated 

treatments to one another.

Stramondo remarked,

I think it would be impossible to make 

judgments about how different technologies 

impact something as complex as quality 

of life. You could make a good judgment 

on Assistive Devices A and B assisting 

with the same function. Wheelchair A and 

B could be better or worse at assisting 

the same function. You could make 

comparisons among treatments with similar 

goals. The problem is when you want to 

compare an anti-nausea medication against 

a new stair-climbing wheelchair. How do you 

decide which one to fund based on which 

improves quality of life more? A concept like 

quality of life is so multidimensional, that’s 

really tricky and probably impossible.266

Ne’eman stated something similar:

There’s no reason why you must conflate 

life extension and disability mitigation into 

a single number. The only reason to do that 

is because they want a measure that can 

be used across categories, [a measure] that 

can compare a cancer and a cystic fibrosis 

drug. If you don’t require comparisons 

across categories, you can use diagnosisspecific measures. . . . I advocate saying, 

“Let’s compare cancer drugs to other 

cancer drugs.”267

Dr. Steve Pearson of ICER stated, “In my 

view, the current system is not working for 

patients, and [they’re] being harmed every 

single day by the fact that the prices for drugs 

and treatments are so poorly aligned for their 

benefits.” He believes it is “healthy for us to help 

force these questions into the forefront and have 

them in public as uncomfortable as they may 

be . . . [it is] important enough given the cost 

and the access problems . . . to try to do it in 

the open and [to] try to use evidence of costeffectiveness as one important anchor [for] that 

discussion.”268 Pearson’s concerns are shared by 

many in the United States.

While these conversations are clearly 

necessary, it is not clear that QALYs are the 

best means of facilitating such conversations. 

There may be alternative means of incorporating 

“value” into healthcare coverage decisions.

68 National Council on Disability
Chapter 6: Recommendations

Congress

When enacting health reform bills, Congress should:

■ Avoid creating provisions of any bill that would require the agency with management and 

oversight responsibilities (such as, for example, HHS) to cover only the most cost-effective 

drugs and treatments, or to require the agency to impose restrictions on less cost-effective 

treatments.

Congress should pass legislation:

■ Prohibiting the use of QALYs by Medicaid and Medicare.

■ Congress should provide funding to HHS for research on best practices on the use of 

cost-effectiveness to inform benefits and coverage decisions with respect to United States 

national health insurance programs, such as Medicare and Medicaid. “Best practices” 

in this case refers to a means of utilizing cost-effectiveness research that facilitates 

greater access to care and does not reduce access to care for people with chronic health 

conditions and disabilities.

■ Congress should fund a report by the Government Accountability Office that examines 

how cost-effectiveness studies influence agency decision making, particularly cost-utility 

analysis (CUA) studies.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 69
Department of Health and Human Services (HHS)

■ HHS should consider including explicitly recruiting people with disabilities and chronic 

illnesses as members of committees and working groups formed to develop effective 

healthcare reform and strategies for lowering the cost of prescription drugs.

■ HHS should support healthcare providers by issuing guidance on what steps to take if their 

patient’s health insurance agency refuses to cover recommended treatment on the basis 

of that treatment’s cost-effectiveness.

US Department of Health and Human Services (HHS) Office for Civil 

Rights (OCR); US Department of Justice (DOJ) Civil Rights Division

■ DOJ and OCR should jointly issue guidance clarifying that the ADA applies to coverage 

programs that states operate, such as Medicaid.

■ OCR, in consultation with DOJ as appropriate, should issue guidance to HHS sub-agencies, 

such as the Centers for Medicare & Medicaid Services as well as to State Medicaid 

Agencies, clarifying that:

● Section 504 and Section 1557 also apply to Medicaid programs because they receive 

federal financial assistance. The guidance should specifically discuss how these 

authorities apply to benefits and reimbursement decisions, and that payment decisions 

should not rely on cost-effectiveness research or reports that are developed using 

QALYs; and

● Section 504 and Section 1557 apply to health insurance programs operated by recipients 

of federal financial assistance from HHS. The guidance should discuss that covered 

health insurance programs should not rely on cost-effectiveness research or reports 

that gather input from the public on health preferences that do not include the input of 

people with disabilities and chronic illnesses.

70 National Council on Disability
HHS Centers for Medicare and Medicaid Services (CMS)

■ CMS should utilize well-established alternatives to QALYs, such as Multicriteria Decision 

Analysis, which is a method that better acknowledges the complexity of healthcare 

coverage decisions, or cost-benefit analysis, when the exact benefits and costs of a drug or 

treatment are known. CMS could utilize these methods in combination, such as using costbenefit analysis as one component of a Multicriteria Decision Analysis. If CMS does utilize 

cost-effectiveness analysis, it should consider utilizing it as one component of a conditionspecific Multicriteria Decision Analysis.

■ CMS should refrain from pursuing means of reducing Medicare and Medicaid prescription 

drug costs that attempt to model US pricing after the pricing in other countries, which may 

heavily rely on QALYs and often deny people with disabilities access to needed care.

■ CMS should rescind the Advanced Notice of Proposed Rulemaking, which proposed an IPI 

for Medicare Part B.

■ CMS should contribute to the development and use of value frameworks that utilize patient 

preferences to define which drugs and treatments are valuable, such as FasterCures’ PPVF.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 71
72 National Council on Disability
Appendix A: Calculation of QALYs Flowchart

Quality-Adjusted Life Years and the Devaluation of Life with Disability 73
74 National Council on Disability
Endnotes

1 Robert P. Navarro, “Changing the Way We Pay for Health Care: Is Value the New Plastic?” Journal of 

Managed Care and Specialty Pharmacy 23, no. 10 (2017): 998–1002.

2 Kimberly Amadeo, “The Rising Cost of Health Care by Year and Its Causes,” The Balance, updated March 12, 

2019, https://www.thebalance.com/causes-of-rising-healthcare-costs-4064878.

3 Centers for Medicare and Medicaid Services (CMS), 2017, “National Health Expenditures 2017 

Highlights,” https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/

NationalHealthExpendData/Downloads/highlights.pdf.

4 Navarro, “Changing the Way We Pay for Health Care,” 998–1002; Partnership to Improve Patient Care (PIPC), 

Measuring Value in Medicine: Uses and Misuses of the QALY: Ethical Issues with QALYs and Alternative 

Measures of Value (Washington, DC: Partnership to Improve Patient Care, June 21, 2017), http://www

.pipcpatients.org/uploads/1/2/9/0/12902828/pipc_white_paper_-_measuring_value_in_medicine_-_uses_and_

misuses_of_the_qaly.pdf.

5 Thomas Sullivan, “Value Frameworks: Are They the Way of the Future?” Policy and Medicine, May 5, 2018, 

https://www.policymed.com/2016/09/value-frameworks-are-they-the-way-of-the-future.html.

6 Institute for Clinical and Economic Review (ICER), A Guide to ICER’s Methods for Health Technology 

Assessment. Boston, Massachusetts: ICER, August 2018, http://icer-review.org/wp-content/uploads/2018/08/

ICER-HTA-Guide_082018.pdf.

7 Tomas Philipson, “EU Vs US Cancer Care: You Get What You Pay For,” Forbes, September 6, 2016, 

https://www.forbes.com/sites/tomasphilipson/2016/09/06/eu-vs-us-cancer-care-you-get-what-you-pay-for/

#3d82a7d66ba5; Ziba Kashef, “Disparities Found in Lung Cancer Care, Survival in US Versus 

England,” YaleNews (blog), May 1, 2018, https://news.yale.edu/2018/05/01/disparities-found-lung-cancercare-survival-us-versus-england.

8 Dan W. Brock, “Ethical Issues in the Use of Cost Effectiveness Analysis for the Prioritization of Health Care 

Resources,” in WHO Guide to Cost Effectiveness Analysis ed. T. Tan-Torres, R. Edejer, Adam T. Baltussen, 

R. Hutubessy, A. Acharya, D. B. Evans, and C. J. L. Murray (Geneva, Switzerland: World Health Organization, 

2003), 291. “Early summary measures of the health status of populations and of the benefits of health 

interventions often assessed only a single variable, such as life expectancy or infant mortality. . . .” Luis Prieto 

and José A. Sacristán, “Problems and Solutions in Calculating Quality Adjusted Life Years (QALYs),” Health 

and Quality of Life Outcomes 1 (2003), doi:10.1186/1477-7525-1-80. “Since health is a function of length of 

life and quality of life. . . . Traditionally, the health of populations has been measured using epidemiological 

indicators, including the presence/absence of disease and/or death (e.g., morbidity and mortality).”

9 “Health Related Quality of Life,” Centers for Disease Control and Prevention, updated October 31, 2018, 

https://www.cdc.gov/hrqol/concept.htm.

10 “Health Related Quality of Life.”

11 “Methods and Measures,” Centers for Disease Control and Prevention, updated October 31, 2018, 

https://www.cdc.gov/hrqol/methods.htm.

12 Sarah Whitehead and Shezad Ali, “Health Outcomes in Economic Evaluation: The QALY and Utilities,” British 

Medical Bulletin 96 (2010): 5, 6. “When faced with such different types of outcome measures arising from 

different interventions, it is difficult to determine where healthcare resources should be most efficiently 

directed. If survival alone is used to differentiate between different healthcare interventions, any impact on 

the quality of life associated with an intervention is ignored.” Timothy Disher, Louis Beaubein, and Marsha 

Campbell-Yeo, “Are Guidelines for Measurement of Quality of Life Contrary to Patient-Centered Care?” 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 75
Journal of Advanced Nursing 74 (2018): 2677, 2678; Brock, “Ethical Issues in the Use of Cost Effectiveness 

Analysis for the Prioritization of Health Care Resources,” 289–90.

13 Whitehead and Ali, “The QALY and Utilities,” 5, 6; Disher, “Patient-Centered Care,” 2677, 2678.

14 Whitehead and Ali, “The QALY and Utilities,” 6.

15 Ari Ne’eman, “Formulary Restrictions Devalue and Endanger the Lives of Disabled People,” HealthAffairs

(blog), HealthAffairs, October 29, 2018, https://www.healthaffairs.org/do/10.1377/hblog20181025.42661/

full/; National Collaborating Centre for Infectious Diseases, National Collaborating Centres for Public Health, 

Understanding Summary Measures Used to Estimate the Burden of Disease: All About HALYs, DALYs, and 

QALYs, Influenza, NCCID Project No. 11, https://nccid.ca/wp-content/uploads/sites/2/2015/03/GBD_Factsheet_

FINAL_E.pdf.

16 Luis Prieto and José A. Sacristán, “Problems and Solutions in Calculating Quality Adjusted Life Years 

(QALYs),” Health and Quality of Life Outcomes 1 (2003), doi:10.1186/1477-7525-1-80 “[T]he change in utility 

value induced by the treatment is multiplied by the duration of the treatment effect to provide the number of 

QALYs gained.” Note the phrase “change in utility value induced by the treatment.” To demonstrate that utility 

values have changed, QALYs would need to be assessed before and after treatment.

17 Ariel Beresniak and Danielle Dupont, “Is There an Alternative to Quality-Adjusted Life Years for Supporting 

Healthcare Decision-Making?” Expert Review of Pharmacoeconomics and Outcomes Research 16, no. 3 

(2016): 353; Whitehead and Ali, “The QALY and Utilities,” 5–6; Marthe R. Gold, David Stevenson, and Dennis 

G. Fryback, “HALYs and QALYs and DALYS, Oh My: Similarities and Differences in Summary Measures 

of Population Health,” Annual Review of Public Health 23 (2002): 116; Tyler M. John, Joseph Millum, and 

David Wasserman, “How to Allocate Scarce Health Resources Without Discriminating Against People with 

Disabilities,” Economics and Philosophy 33, no. 2 (2016): 161–86.

18 Beresniak and Dupont, “Is There an Alternative to Quality-Adjusted Life Years,” 353. Some researchers take 

issue with defining CUAs as a type of cost-effectiveness study.

19 “Incremental Cost-Effectiveness Ratio (ICER),” York Health Economics Consortium, updated 2016, 

https://www.yhec.co.uk/glossary/incremental-cost-effectiveness-ratio-icer/.

20 Elliot Marseille, Bruce Larson, Dhruv S. Kazi, James G. Kahn, and Sidney Rosen, “Thresholds for the CostEffectiveness of Interventions: Alternative Approaches,” Bulletin of the World Health Organization 93 

(2015): 118.

21 Ceri Phillips and Guy Thompson, “What Is Cost-Effectiveness?” Hayward Medical Communications What 

Is . . .? Series (2nd ed.), February 2009, http://www.bandolier.org.uk/painres/download/whatis/Cost-effect

.pdf; Christopher McCabe, “What Is Cost-Utility Analysis?” Hayward Medical Communications What Is . . .? 

Series (2nd ed.), February 2009, http://www.bandolier.org.uk/painres/download/whatis/What_is_cost-util.pdf; 

“Measuring Burden of Disease: The Concept of QALYs and DALYs,” Eufic, December 1, 2011, 

https://www.eufic.org/en/understanding-science/article/measuring-burden-of-disease-the-concept-of-qalysand-dalys; ”Incremental Cost-Effectiveness Ratio (ICER),” York Health Economics Consortium, updated 

2016, https://www.yhec.co.uk/glossary/incremental-cost-effectiveness-ratio-icer/.

22 “About EQ-5D,” EQ-5D, EuroQoL Group, updated April 28, 2017, https://euroqol.org/eq-5d-instruments/.

23 Greg Bognar, “QALYs, DALYs, and Their Critics,” in The Routledge Companion to Bioethics, ed. John D. 

Arras, Elizabeth Fenton, and Rebecca Kukla (New York: Routledge, 2015), 47; George Gillett, 

“NHS Drugs, Aristotle and Health Economics: The Problem of Quantifying the Value of Life,” 

New Statesman America, August 18, 2014, https://www.newstatesman.com/health/2014/08/nhs-drugsaristotle-and-health-economics-problem-quantifying-value-life.

24 Reza Goudarzi et al., “Population-Based Preference Weights for the EQ-5D Health States Using the Visual 

Analogue Scale (VAS) in Iran,” Iranian Red Crescent Medical Journal 18 (2016), doi:10.5812/ircmj.21584.

25 Chunmei Wu et al., “Chinese Version of the EQ-5D Preference Weights: Applicability in a Chinese General 

Population,” PloS ONE 11, no. 10 (2016): e0164334, doi:https://doi.org/10.1371/journal.pone.0164334

76 National Council on Disability
26 Whitehead and Ali, “The QALY and Utilities,” 8.

27 Ariel Beresniak et al., “Advantages and Limitations of Utility Assessment Methods in Rheumatoid Arthritis,” 

The Journal of Rheumatology 34 (2007): 2194.

28 Partnership to Improve Patient Care (PIPC), Measuring Value in Medicine: Uses and Misuses of the QALY: 

Ethical Issues with QALYs and Alternative Measures of Value, (Washington, DC: Partnership to Improve 

Patient Care, June 21, 2017), http://www.pipcpatients.org/uploads/1/2/9/0/12902828/pipc_white_paper_-_

measuring_value_in_medicine_-_uses_and_misuses_of_the_qaly.pdf.

29 Partnership to Improve Patient Care, 8; John Horsman, William Furlong, David Feeny, and George Torrance, 

“The Health Utilities Index (HUI®): Concepts, Measurement Properties, and Applications,” Health and Quality 

of Life Outcomes 1 (2003): 54. The most common questionnaires used are the Euro-QoL 5D (EQ-5D), the 

Health Utilities Index, the SF-6D, and The Quality of Well-Being Scale.

30 Whitehead and Ali, “The QALY and Utilities,” 11.

31 Gunnar Nemeth, “Health related quality of life outcome instruments,” European Spine Journal 15, suppl. 1 

(2006): S47.

32 “About EQ-5D,” EQ-5D, EuroQoL Group, updated April 28, 2017, https://euroqol.org/eq-5d-instruments/.

33 “EQ-5D-3L: About,” EQ-5D, EuroQoL Group, updated April 18, 2017, https://euroqol.org/eq-5d-instruments/

eq-5d-3l-about/.

34 EuroQoL Group, EQ-5D-3L User Guide: Basic Information on How to Use the EQ-5D-3L Instrument

(Rotterdam, Netherlands: EuroQol Group, 2015), https://euroqol.org/wp-content/uploads/2016/09/EQ-5D-3L_

UserGuide_2015.pdf.

35 Stephen M. Campbell, Joseph A. Stramondo, “The Complicated Relationship of Disability and Well-Being,” 

Kennedy Institute of Ethics Journal 27, no. 2 (2017): 156–60. Campbell and Stramondo explain that, from an 

ethical standpoint, disability is neither intrinsically bad (i.e., having short stature or cognitive disabilities are 

not bad in and of themselves), nor instrumentally bad (i.e., disability does not prevent a large percentage 

of intrinsically good things from happening nor cause a large number of intrinsically bad things to happen). 

The two authors also note in a series of vignettes that whether disability does actually negatively impact 

quality of life (and whether the person perceives it as doing so) has more to do with the social and economic 

circumstances surrounding the disability than it does with the impairments.

36 EuroQoL Group, EQ-5D-3L User Guide.

37 EuroQoL Group, EQ-5D-3L User Guide.

38 EuroQoL Gropup, EQ-5D-3L User Guide, 7.

39 Marthe R. Gold, David Stevenson, and Dennis G. Fryback, “HALYs and QALYs and DALYS, Oh My,” 118–19; 

Keith Tolley, “What Are Health Utilities?” (2nd ed.), Hayward Medical Communications What Is . . .? Series,

http://www.bandolier.org.uk/painres/download/whatis/Health-util.pdf.

40 Bognar, “QALYs, DALYs, and Their Critics,” 47.

41 Benjamin M. Craig, A. Simon Pickard, Elly Stolk, and John E. Brazier, “U.S. Valuation of the SF-6D,” Medical 

Decision-Making 33, no. 6 (2013): 793–803.

42 C.A. Marra et. al., “Not All ‘Quality-Adjusted Life Years’ Are Equal,” Journal of Clinical Epidemiology 60 (2007): 

616–24; Christine McDonough and Anna N. A. Tosteson, “Measuring Preferences for Cost-Utility Analysis: 

How Choice of Method May Influence Decision-Making,” Pharmacoeconomics 25, no. 2 (2007): 93–106.

43 Whitehead and Ali, “The QALY and Utilities,” 11 (“Once completed, the questionnaires generate a score using 

an algorithm based on values that have been obtained from a sample of the general public”); Tolley, “What 

Are Health Utilities?” 4–5 (“By far the most well-known indirect method is the generic utility instrument, 

whereby a set of non-disease-specific health states, based on a combination of general attributes, have been 

valued by a general public sample . . . Patients with any health condition then complete a simple questionnaire 

which defines the generic health state they are in, and the appropriate utility from the scoring algorithm is 

applied”).

Quality-Adjusted Life Years and the Devaluation of Life with Disability 77
44 “Value Sets,” EQ-5D, EuroQoL Group, https://euroqol.org/publications/key-euroqol-references/value-sets/.

45 Whitehead and Ali, “The QALY and Utilities,” 16.

46 Whitehead and Ali, “The QALY and Utilities,” 16.

47 Whitehead and Ali, “The QALY and Utilities,” 16.

48 Disher, Beaubein, and Yeo, “Patient Centered Care,” 2679.

49 Alex G. Garza and Kathleen W. Wyrwich, “Health Utility Measures and the Standard Gamble,” Academic 

Emergency Medicine 10, no. 4 (2003): 360–63.

50 Garza and Wyrwich, “Standard Gamble,” 361; Disher, Beaubein, and Yeo, “Patient Centered Care,” 2679.

51 Garza and Wyrwich, “Standard Gamble,” 361–62.

52 Garza and Wyrwich, “Standard Gamble,” 361.

53 Tyler M. John, Joseph Millum and David Wasserman, “How to Allocate Scarce Health Resources without 

Discriminating Against People with Disabilities,” Economics and Philosophy 33, no. 2 (2016): 161–86.

54 NCD interview with Dr. Steve Pearson, February 1, 2019.

55 NCD interview with David Wasserman, PhD, January 15, 2009

56 R. Kirkdale, J. Krell, C. O’ Hanlon-Brown, M. Tuthill, J. Waxman, “The cost of a QALY,” QJM: An International 

Journal of Medicine 103 no. 9 (2010): 715-720; Douglas K. Owens, “Interpretation of Cost-Effectiveness 

Analyses,” Journal of General Internal Medicine 13, no. 10 (1998): 716–17.

57 Generics and Biosimilars Initiative, “What Is the Incremental Cost Effectiveness Ratio (ICER?)” March 12, 

2010, http://www.gabionline.net/Generics/General/What-is-the-incremental-cost-effectiveness-ratio-ICER.

58 “What Is Palliative Care?” Get Palliative Care, updated 2019, https://getpalliativecare.org/whatis/.

59 “What Is Palliative Care?” Get Palliative Care, updated 2019, https://getpalliativecare.org/whatis/.

60 Anne B. Wichmann et al., “The Use of Quality-Adjusted Life Years in Cost-Effectiveness Analyses in Palliative 

Care: Mapping the Debate Through an Integrative Review,” Palliative Medicine 31, no. 4 (2017): 309–10.

61 Anne B. Wichmann et al., “Palliative Care,” 310–11.

62 NCD interview with Dr. Steve Pearson, February 1, 2019.

63 Y. Tony Yang and Margaret M. Mahon, “Palliative Care for the Terminally Ill in America: The Consideration of 

Qalys, Costs, and Ethical Issues,” Medicine, Health Care and Philosophy 15, no. 4 (2012): 413.

64 Yang and Mahon, “Palliative Care for the Terminally Ill in America,” 414.

65 Anne B. Wichmann et al., “Palliative Care,” 313–14; Charles Normand, “Limitations of QALYs and the Road to 

PalYs,” 29–30.

66 Yang and Mahon, “Palliative Care for the Terminally Ill in America,” 414–15.

67 Stephen Barrie, “QALYs, Euthanasia, and the Puzzle of Death,” Journal of Medical Ethics 41, no. 8 (2014): 635–38.

68 Barrie, “QALYs, Euthanasia, and the Puzzle of Death,” 635–38.

69 Tara A. Lavelle et al., “Patient Variability Seldom Assessed in Cost-Effectiveness Studies,” Medical DecisionMaking 38, no. 4 (2018): 488.

70 Lavelle et al, “Patient Variability Seldom Assessed,” 489.

71 Lavelle et al., “Patient Variability Seldom Assessed,” 487.

72 Lavelle et al., “Patient Variability Seldom Assessed,” 491–92.

73 Ari Ne’eman, “Formulary Restrictions”; National Collaborating Centre for Infectious Diseases, National 

Collaborating Centres for Public Health, “Understanding Summary Measures Used to Estimate the Burden of 

Disease: All About HALYs, DALYs, and QALYs.”

74 Disher, Beaubein, and Yeo, “Patient Centered Care,” 2679.

75 NCD Interview with David Wasserman, January 15, 2019.

76 Wendy Hensel and Leslie E. Wolf, “Playing God: The Legality of Plans Denying Scarce Resources to People 

with Disabilities in Public Health Emergencies,” Florida Law Review 63 (2011): 755.

77 Adrienne W. Scott et al., “Public Attitudes About Eye and Vision Health.” JAMA Ophthalmology 134, no. 10 

(2016): 1111–18.

78 National Council on Disability
78 Scott et al., “Public Attitudes About Eye and Vision Health,” 1111–18.

79 Sean Sinclair, “How to Avoid Unfair Discrimination Against Disabled Patients in Healthcare Resource 

Allocation,” Journal of Medical Ethics 38 (2011): 158–59.

80 D. Lule et al., “Life Can Be Worth Living in Locked-In Syndrome,” Progress in Brain Research 177 (2009): 

341–43, 346–47.

81 S. Feinman, “The Blind as ‘Ordinary People’,” Journal of Visual Impairment & Blindness 72, no. 6 (1979): 231–38.

82 Dirksen Bauman and Joseph J. Murray, “An Introduction to Deaf Gain: Shifting Our Perceptions of Deaf People 

from Hearing Loss to Deaf Gain,” Psychology Today (blog), November 13, 2014, https://www.psychologytoday

.com/us/blog/deaf-gain/201411/introduction-deaf-gain.

83 John Harris, “QALYfying the Value of Life,” Journal of Medical Ethics 13 (1987): 117–23.

84 Harris, “QALYfying the Value of Life,” 120.

85 Harris, “QALYfying the Value of Life,” 120.

86 Harris, “QALYfying the Value of Life,” 122.

87 Ari Ne’eman, “Formulary Restrictions”; Tony Coelho, “Patients Harmed by ‘Cost-Effectiveness’ Measures,” 

RealClearHealth, August 30, 2018, https://www.realclearhealth.com/articles/2018/08/30/patients_harmed_by_

costeffectiveness_measures_110821.html.

88 Ari Ne’eman, “Formulary Restrictions.”

89 Ari Ne’eman, “Formulary Restrictions.”

90 Ari Ne’eman, “Formulary Restrictions.”

91 Bognar, “QALYs, DALYs, and Their Critics,” 52.

92 Bognar, “QALYs, DALYs, and Their Critics,” 52.

93 Bognar, “QALYs, DALYs, and Their Critics,” 52.

94 Bognar, “QALYs, DALYs, and Their Critics,” 52.

95 Beresniak and Dupont, “Is There an Alternative to Quality-Adjusted Life Years for Supporting Healthcare 

Decision-Making?” 353; Whitehead and Ali, “The QALY and Utilities,” 5–6; Gold, Stevenson, and Fryback, 

“HALYs and QALYs and DALYS, Oh My,” 116; John, Millum, and Wasserman, “How to Allocate Scarce Health 

Resources,” 161–86.

96 Harris, “QALYfying the Value of Life,” 120.

97 Harris, “QALYfying the Value of Life,” 120.

98 John Harris, “It’s Not NICE to Discriminate,” Journal of Medical Ethics 31 (2005): 373.

99 Peter J. Neumann and Dan Greenberg, “Perspective: Is the United States Ready for QALYS?” Health Affairs

28, no. 5 (2009): 1369.

100 Fritz Alhoff, “The Oregon Plan and QALYs,” Ethics Journal of the American Medical Association 7, no. 2 

(February 2005): 1.

101 Alhoff, “The Oregon Plan and QALYs,” 1–2.

102 Alhoff, “The Oregon Plan and QALYs,” 1–2.

103 Alhoff, “The Oregon Plan and QALYs,” 1–2.

104 Jerome Bickenbach, “Disability and Health Care Rationing,” The Stanford Encyclopedia of Philosophy

(Spring 2016 Edition), Edward N. Zalta (ed.), https://plato.stanford.edu/archives/spr2016/entries/disabilitycare-rationing/.

105 Robert Pear, “White House Expected to Back Oregon’s Health-Care Rationing,” New York Times, March 18, 

1993, pg. 00001, https://www.nytimes.com/1993/03/18/us/white-house-expected-to-back-oregon-s-healthcare-rationing.html?module=inline.

106 Louis W. Sullivan, “Oregon Health Plan Is Unfair to the Disabled,” letter to the editor, New York Times,

September 1, 1992.

107 Aaron E. Caroll, “Forbidden Topic in Health Policy Debate: Cost Effectiveness,” New York Times, 

December 15, 2014, https://www.nytimes.com/2014/12/16/upshot/forbidden-topic-in-health-policy-debateQuality-Adjusted Life Years and the Devaluation of Life with Disability 79
cost-effectiveness.html; Philip A. Perry and Timothy Hotze, “Oregon’s Experiment with Prioritizing Public 

Health Care Services,” AMA Journal of Ethics (blog), April 2011, https://journalofethics.ama-assn.org/article/

oregons-experiment-prioritizing-public-health-care-services/2011-04.

108 Philip Elis, Colin Baker, and Morgan Hanger, Research on the Comparative Effectiveness of Medical 

Treatments: Issues and Options for an Expanded Federal Role, edited by John Skeen, US Congressional 

Budget Office, Pub. No. 2975, December 2007, http://www.cbo.gov/sites/default/files/cbofiles/ftpdocs/88xx/

doc8891/12-18-comparativeeffectiveness.pdf.

109 Elis, Baker, and Hanger, Research on the Comparative Effectiveness of Medical Treatments, 2–3.

110 Elis, Baker, and Hanger, Research on the Comparative Effectiveness of Medical Treatments, 2–3.

111 Elis, Baker, and Hanger, Research on the Comparative Effectiveness of Medical Treatments, 26.

112 Matthew Adler, “QALYS and Policy Evaluation: A New Perspective,” Yale Journal of Health Policy, Law, and 

Ethics 6 (2006): 3–6.

113 Adler, “QALYs and Policy Evaluation,” 5–6.

114 Adler, “QALYs and Policy Evaluation,” 3–6.

115 42 U.S. Code § 1320e-1(e).

116 42 U.S. Code § 1320e-1(e).

117 42 U.S. Code § 1320e-1(c)(1).

118 42 U.S. Code § 1320e-1(c)(1).

119 Govind Persad, “Priority-Setting, Cost Effectiveness, and the Affordable Care Act,” American Journal of Law 

and Medicine 41, no. 1 (2015): 136–40.

120 NCD Interview with David Wasserman, January 15, 2019.

121 Institute for Clinical and Economic Review, “The Institute for Clinical and Economic Review to Collaborate 

with the Department of Veterans Affairs’ Pharmacy Benefits Management Services Office,” June 27, 2017, 

https://icer-review.org/announcements/va-release/.

122 C. Bernie Good, Tom Emmendorfer, and Michael Valentino, “VA Responds to Concerns About Collaboration 

with ICER,” HealthAffairs (blog), HealthAffairs, October 25, 2017, https://www.healthaffairs.org/do/10.1377/

hblog20171024.745943/full/.

123 Good, Emmendorfer, and Valentino, “VA Responds to Concerns about Collaboration with ICER.”

124 Louis P. Garrison, “Cost-Effectiveness and Clinical Practice Guidelines: Have We Reached a Tipping Point?—

An Overview, Value in Health 19, no. 5 (2016): 513.

125 Garrison, “Have We Reached a Tipping Point?” 513.

126 Peter J. Neumann and Dan Greenberg, “Perspective: Is the United States Ready for QALYS?” Health Affairs

28, no. 5 (2009): 1369.

127 Peter J. Neumann et al., “The Changing Face of the Cost-Utility Literature, 1990–2012,” Value in Health 18, 

no. 2 (2015): 277.

128 National Health Council, The Patient Voice in Value: The National Health Council Patient-Centered Value Model 

Rubric (Washington, DC: National Health Council, March 2016), http://www.nationalhealthcouncil.org/sites/

default/files/Value-Rubric.pdf.

129 Brian Solow and Edmund J. Pezalla, “Commentary: ISPOR’s Initiative on US Value Assessment Frameworks: 

The Use of Cost-Effectiveness Research in Decision Making Among US Insurers.” Value in Health 21 (2018): 166.

130 Solow and Pezalla, “The Use of Cost Effectiveness Research in Decision Making,” 166.

131 Solow and Pezalla, “The Use of Cost-Effectiveness Research in Decision Making,” 167.

132 Solow and Pezalla, “The Use of Cost-Effectiveness Research in Decision Making,” 167.

133 Solow and Pezalla, “The Use of Cost Effectiveness Research in Decision Making,” 167.

134 CVS Health, Current and New Approaches to Making Drugs More Affordable, August 2018, https://cvshealth

.com/sites/default/files/cvs-health-current-and-new-approaches-to-making-drugs-more-affordable.pdf, 8.

135 Ari Ne’eman, interview with Kelly Israel, November 27, 2018.

80 National Council on Disability
136 Matthew Harper, “Opposite Day: Drug May Save Lives, So Drugmakers Offer to Cut Price,” Forbes, March 10, 

2018, https://www.forbes.com/sites/matthewherper/2018/03/10/sales-flopped-but-does-this-heart-drugsave-lives/#75f7748a7580; Michael O’ Riordan, “PCSK9 Inhibitors Not Cost-Effective at Current Price: ICER 

Review,” Medscape, September 9, 2015, https://www.medscape.com/viewarticle/850715#vp_1.

137 Sara van Geertruyden, interview with Kelly Israel, November 28, 2018.

138 Harper, “Opposite Day”; O’ Riordan, “PCSK9 Inhibitors Not Cost-Effective.”

139 Harper, “Opposite Day.”

140 Harper, “Opposite Day”; O’ Riordan, “PCSK9 Inhibitors Not Cost-Effective.”

141 Gillett, “NHS Drugs, Aristotle, and Health Economics.”

142 Gillett, “NHS Drugs, Aristotle, and Health Economics.”

143 Gillett, “NHS Drugs, Aristotle, and Health Economics.”

144 Steve Iliffe, “Thriving on Challenge: NICE’s Dementia Guidelines,” Expert Review of Pharmacoeconomics and 

Outcomes Research 7, no. 6 (2007): 535; “NICE Guidance,” National Institute of Health and Care Excellence, 

updated 2019, https://www.nice.org.uk/guidance.

145 Sarah Long, “Squashed Dreams and Rare Breeds: Ableism and the Arbiters of Life and Death,” Disability and 

Society 30 (2015): 1118–22.

146 Kathy Hugues and Nikita Jeswani, “HTA Oncology Recommendations Have Grown More Restrictive Over 

Time,” Avalere, June 1, 2018, https://avalere.com/insights/htas-recommendations-for-oncology-have-grownmore-restrictive-over-time.

147 Tomas Philipson, “EU Vs US Cancer Care: You Get What You Pay For,” Forbes, September 6, 2016, 

https://www.forbes.com/sites/tomasphilipson/2016/09/06/eu-vs-us-cancer-care-you-get-what-you-payfor/#3d82a7d66ba5.

148 Ziba Kashef, “Disparities Found in Lung Cancer Care, Survival in U.S. Versus England,” YaleNews (blog), 

May 1, 2018, https://news.yale.edu/2018/05/01/disparities-found-lung-cancer-care-survival-us-versus-england.

149 J. G. Taylor, “NICE, Alzheimer’s, and the QALY,” Clinical Ethics 2 (2007): 51.

150 “Alzheimer’s Disease Fact Sheet,” National Institute on Aging, National Institutes of Health, updated 

August 17, 2016, https://www.nia.nih.gov/health/alzheimers-disease-fact-sheet.

151 “Medications for Memory,” Alzheimer’s Association, updated 2019, https://www.alz.org/alzheimers-dementia/

treatments/medications-for-memory.

152 Jenny Hope, “Alzheimer’s Victory for the Mail: Now Just £2.50 Can Buy a Life After U-Turn on Drugs Banned 

by NICE,” Daily Mail, October 7, 2010, https://www.dailymail.co.uk/health/article-1318360/Alzheimers-sufferersfinally-vital-2-50-drugs-banned-NICE.html#ixzz11f4t0r9d.

153 Taylor, “NICE, Alzheimer’s, and the QALY,” 51.

154 Clare Dyer, “NICE Faces Legal Challenge over Alzheimer’s Drug,” BMJ News 334 (2007): 654–55; Hope, 

“Alzheimer’s Victory for the Mail.”

155 Taylor, “NICE, Alzheimer’s, and the QALY,” 51–52; Hope, “Alzheimer’s Victory for the Mail,”; Iliffe, “Thriving 

on Challenge,” 535–36; Steve Iliffe, “The National Institute for Health and Clinical Excellence (NICE) and 

Drug Treatment for Alzheimer’s Disease,” CNS Drugs 21, no. 3 (2007): 177; Harris, “It’s Not NICE to 

Discriminate,” 373.

156 Royal College of Psychiatrists, “Appeal from the Royal College of Psychiatrists and the British Geriatrics 

Society Regarding the NICE Final Appraisal Document: Donepezil, Rivastigmine, Galantamine and 

Memantine for the Treatment of Alzheimer’s Disease,” https://www.nice.org.uk/guidance/ta111/documents/

appeals-received-from-the-royal-college-of-psychiatrists-british-geriatrics-society-joint-appeal2.

157 Iliffe, “Drug Treatment for Alzheimer’s Disease,” 181.

158 Iliffe, “Drug Treatment for Alzheimer’s Disease,” 179.

159 Royal College of Psychiatrists, “Appeal from the Royal College of Psychiatrists and the British Geriatrics 

Society Regarding the NICE Final Appraisal Document: Donepezil, Rivastigmine, Galantamine and 

Quality-Adjusted Life Years and the Devaluation of Life with Disability 81
Memantine for the Treatment of Alzheimer’s Disease,” https://www.nice.org.uk/guidance/ta111/documents/

appeals-received-from-the-royal-college-of-psychiatrists-british-geriatrics-society-joint-appeal2.

160 Iliffe, “Thriving on Challenge,” 536.

161 Dyer, “NICE Faces Legal Challenge,” 654–55.

162 Owen Dyer, “High Court upholds NICE decision to limit treatments for Alzheimer’s disease,” BMJ News 335 

(2007): 319.

163 Hope, “Alzheimer’s victory for the Mail.”

164 National Institute for Health and Care Excellence, “Donepezil, Galantamine, Rivastigmine and Memantine for 

the Treatment of Alzheimer’s Disease,” National Institute for Health and Care Excellence, updated June 20, 

2018, https://www.nice.org.uk/guidance/ta217/chapter/1-Guidance.

165 Sarah Boseley, “Patients Suffer When NHS Buys Expensive New Drugs, Says Report,” The Guardian, 

February 18, 2015, https://www.theguardian.com/society/2015/feb/19/nhs-buys-expensive-new-drugsnice-york-karl-claxton-nice.

166 “Cystic Fibrosis,” Mayo Clinic, October 13, 2016, https://www.mayoclinic.org/diseases-conditions/cysticfibrosis/symptoms-causes/syc-20353700.

167 Girish D. Sharma, “Cystic Fibrosis,” Medscape, last updated October 30, 2018, https://emedicine.medscape

.com/article/1001602-overview.

168 UK Cystic Fibrosis Trust, “UK Cystic Fibrosis Treasury: Annual Data Report 2017,” August 2018.

169 “Mucus Thinners,” Cystic Fibrosis Foundation, https://www.cff.org/Life-With-CF/Treatments-and-Therapies/

Medications/Mucus-Thinners/.

170 “CFTR Modulator Therapies,” Cystic Fibrosis Foundation, https://www.cff.org/Life-With-CF/Treatmentsand-Therapies/Medications/CFTR-Modulator-Therapies/.

171 “CFTR Modulator Therapies,” Cystic Fibrosis Foundation.

172 “CFTR Modulator Therapies,” Cystic Fibrosis Foundation.

173 Vertex Pharmaceuticals Incorporated, “FDA Approves ORKAMBITM (lumacaftor/ivacaftor)—The First 

Medicine to Treat the Underlying Cause of Cystic Fibrosis for People Ages 12 and Older with Two Copies 

of the F508del Mutation,” July 2, 2015, https://investors.vrtx.com/news-releases/news-release-details/

fda-approves-orkambitm-lumacaftorivacaftor-first-medicine-treat.

174 National Institute for Health and Care Excellence, Lumacaftor–Ivacaftor for Treating Cystic Fibrosis 

Homozygous for the F508del Mutation, National Institute for Health and Care Excellence, July 27, 2016, 

https://www.nice.org.uk/guidance/ta398/chapter/3-Evidence.

175 National Institute for Health and Care Excellence, “The Guidelines Manual: Assessing Cost Effectiveness,” 

November 2012, https://www.nice.org.uk/process/pmg6/chapter/assessing-cost-effectiveness.

176 National Institute for Health and Care Excellence, Single Technology Appraisal: Lumacaftor and Ivacaftor 

Combination Therapy for Treating Cystic Fibrosis Homozygous for the F508del Mutation, February 2016, 

https://www.nice.org.uk/guidance/ta398/documents/committee-papers; UK Cystic Fibrosis Trust, UK Cystic 

Fibrosis Treasury: Annual Data Report 2017, August 2018.

177 National Institute for Health and Care Excellence, Single Technology Appraisal: Lumacaftor and Ivacaftor 

Combination Therapy for Treating Cystic Fibrosis Homozygous for the F508del Mutation, https://www.nice

.org.uk/guidance/ta398/chapter/4-Committee-discussion.

178 National Institute for Health and Care Excellence, Lumacaftor–Ivacaftor for Treating Cystic Fibrosis 

Homozygous for the F508del Mutation, National Institute for Health and Care Excellence, July 27, 2016.

179 National Institute for Health and Care Excellence, Lumacaftor–Ivacaftor for Treating Cystic Fibrosis 

Homozygous for the F508del Mutation.

180 Institute for Clinical and Economic Review, Modulator Treatments for Cystic Fibrosis: Effectiveness 

and Value, June 7, 2018, https://icer-review.org/wp-content/uploads/2017/10/CF_Final_Evidence_

Report_06082018.pdf.

82 National Council on Disability
181 Institute for Clinical and Economic Review, Modulator Treatments for Cystic Fibrosis: Effectiveness and Value, 62.

182 Institute for Clinical and Economic Review, Modulator Treatments for Cystic Fibrosis: Effectiveness and Value, 62.

183 Institute for Clinical and Economic Review, Modulator Treatments for Cystic Fibrosis: Effectiveness and 

Value, ES18.

184 Andrew McConaghie, “The Orkambi Blame Game,” PMLiVE, April 10, 2019, https://www.pmlive.com/

pharma_intelligence/The_Orkambi_blame_game_1283755.

185 McConaghie, “The Orkambi Blame Game.”

186 McConaghie, “The Orkambi Blame Game.”

187 McConaghie, “The Orkambi Blame Game.”

188 Medicare Program; International Pricing Index Model for Medicare Part B Drugs. Federal Register. 83 Fed. 

Reg. 54546 (proposed October 30, 2018) (to be codified at 42 CFR Chapter IV).

189 J. F. O’ Mahoney and D. Coughlan, “The Irish Cost-Effectiveness Threshold: Does It Support Rational 

Rationing or Might It Lead to Unintended Harm to Ireland’s Health System?” Pharmacoeconomics 34, no. 1 

(2016): 5–11.

190 National Collaborating Centre for Infectious Diseases, National Collaborating Centres for Public Health, 

Understanding Summary Measures Used to Estimate the Burden of Disease: All About HALYs, DALYs, and 

QALY, Influenza, NCCID Project No. 11, https://nccid.ca/wp-content/uploads/sites/2/2015/03/GBD_Factsheet_

FINAL_E.pdf.

191 Ed Silverman, “CVS and the $100,000 QALY,” Managed Care Magazine, November 24, 2018, https://www

.managedcaremag.com/archives/2018/12/cvs-and-100000-qaly.

192 “Our Industry,” Pharmaceutical Care Management Association, updated 2019, https://www.pcmanet.org/

our-industry/.

193 Brittany Hoffman-Eubanks, “The Role of Pharmacy Benefit Managers in American Health Care: Pharmacy 

Concerns and Perspectives: Part 1,” Pharmacy Times, November 14, 2017, https://www.pharmacytimes.com/

news/the-role-of-pharmacy-benefit-mangers-in-american-health-care-pharmacy-concerns-and-perspectivespart-1.

194 Hoffman-Eubanks, “The Role of Pharmacy Benefit Managers in American Health Care.”

195 Hoffman-Eubanks, “The Role of Pharmacy Benefit Managers in American Health Care.”

196 “Our Industry,” Pharmaceutical Care Management Association, updated 2019, https://www.pcmanet.org/

our-industry/.

197 Ari Ne’eman, interview with Kelly Israel, November 27, 2018.

198 Nancy L. Yu, Presten Atteberry, and Peter B. Bach, “Spending on Prescription Drugs in the US: Where 

Does All the Money Go?” HealthAffairs (blog), HealthAffairs, July 31, 2018, https://www.healthaffairs.org/

do/10.1377/hblog20180726.670593/full/.

199 CVS Health, Current and New Approaches to Making Drugs More Affordable, August 2018, https://cvshealth

.com/sites/default/files/cvs-health-current-and-new-approaches-to-making-drugs-more-affordable.pdf, 8.

200 CVS Health, “Current and New Approaches,” 9.

201 CVS Health, “Current and New Approaches,” 9.

202 CVS Health, “Current and New Approaches,” 10.

203 CVS Health, “Current and New Approaches,” 10.

204 Troyen Brennan and Surya Singh, “Why CVS Is Giving Plans a New Tool to Target High Launch Prices,” 

Health Affairs (blog), HealthAffairs, September 17, 2018, https://www.healthaffairs.org/do/10.1377/

hblog20180913.862850/full/.

205 CVS Health, “Current and New Approaches,” 10; US Food and Drug Administration, “Fact Sheet: 

Breakthrough Therapies,” updated March 28, 2018, https://www.fda.gov/RegulatoryInformation/

LawsEnforcedbyFDA/SignificantAmendmentstotheFDCAct/FDASIA/ucm329491.htm.

206 CVS Health, “Current and New Approaches,” 10.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 83
207 Max Nisen, “CVS’s Drug Price Plan Lets Pharma Off Too Easy,” Bloomberg Opinion, August 17, 2018, 

https://www.bloomberg.com/opinion/articles/2018-08-17/cvs-drug-price-plan-lets-pharma-off-too-easy.

208 Nisen, “Plan Lets Pharma Off Too Easy.”

209 Dylan Scott, “One Neat Trick for Forcing Pharma to Set Lower Drug Prices,” Vox, September 17, 2018, 

https://www.vox.com/policy-and-politics/2018/9/17/17871024/cvs-pharma-lower-drug-prices.

210 Scott, “One Neat Trick.”

211 Scott, “One Neat Trick.”

212 Robert W. Dubois, “CVS to Restrict Patient Access Using Cost-Effectiveness: Too Much, Too Soon,” 

HealthAffairs (blog), HealthAffairs, September 17, 2018, https://www.healthaffairs.org/do/10.1377/

hblog20180913.889578/full/.

213 Dubois, “Too Much, Too Soon.”

214 For an explanation as to why two different subgroups of patients would produce two different cost-per-QALY 

outcomes, reference the section “Cost Per QALY.”

215 Dubois, “Too Much, Too Soon.”

216 Tony Coelho, “Patients Harmed by ‘Cost-Effectiveness’ Measures,” RealClearHealth, August 30, 2018, 

https://www.realclearhealth.com/articles/2018/08/30/patients_harmed_by_cost-effectiveness_

measures_110821.html.

217 Andrew Dunn, “Patient Groups Attack CVS Use of ICER Metrics, Urge Rethink,” BioPharmaDive,

September 14, 2018, https://www.biopharmadive.com/news/cvs-adopts-icer-metrics-in-shift-tovalue-based-drug-pricing/530181/.

218 Ne’eman, “Formulary Restrictions.”

219 Joshua Cohen, “Will CVS Caremark Make ICER the American NICE?” Forbes, September 20, 2018, 

https://www.forbes.com/sites/joshuacohen/2018/09/20/will-cvs-caremark-make-icer-the-americannice/#20b50d326173.

220 Ed Silverman, “Facing Criticism, CVS May Modify Its New Cost-Effectiveness Program for Covering 

Some Drugs,” STAT News, September 18, 2018, https://www.statnews.com/pharmalot/2018/09/18/

cvs-cost-effectiveness-coverage/.

221 Brennan and Singh, “Why CVS Is Giving Plans a New Tool.”

222 Brennan and Singh, “Why CVS Is Giving Plans a New Tool.”

223 Brennan and Singh, “Why CVS Is Giving Plans a New Tool.”

224 Dubois, “Too Much, Too Soon.”

225 Silverman, “Facing Criticism, CVS May Modify Its New Cost-Effectiveness Program.”

226 Silverman, “Facing Criticism.”

227 Silverman, “Facing Criticism.”

228 Beresniak and Dupont, “Is There an Alternative to Quality-Adjusted Life Years?” 352–53; Scott D. Grosse, 

Steven M. Teutsch, and Anne C. Haddix, “Lessons from Cost-Effectiveness Research for United States Public 

Health Policy,” Annual Review of Public Health 28 (2007): 370–71.

229 Grosse, Teutsch, and Haddix, “Lessons from Cost-Effectiveness Research,” 370.

230 Beresniak and Dupont, “Is There an Alternative to Quality Adjusted Life Years?” 352.

231 Jeremy Laurance, “The Cost of NHS Health Care: Deciding Who Lives and Who Dies,” Independent, March 9, 

2015, https://www.independent.co.uk/life-style/health-and-families/features/the-cost-of-nhs-health-caredeciding-who-lives-and-who-dies-10096784.html.

232 Beresniak and Dupont, “Is There an Alternative to Quality Adjusted Life Years?” 352; Grosse, Teutsch, and 

Haddix, “Lessons from Cost Effectiveness Research,” 366; Navarro, “Is Value the New Plastic?” 999.

233 Grosse, Teutsch, and Haddix, “Lessons from Cost Effectiveness Research,” 366; Joe Craven McGinty, “Why 

the Government Puts a Dollar Value on Life,” Wall Street Journal, March 25, 2016, https://www.wsj.com/

articles/why-the-government-puts-a-dollar-value-on-life-1458911310.

84 National Council on Disability
234 Grosse, Teutsch, and Haddix, “Lessons from Cost Effectiveness Research,” 366.

235 Adler, “QALYs and Policy Evaluation,” 4–5.

236 Grosse, Teutsch, and Haddix, “Lessons from Cost Effectiveness Research,” 366.

237 Beresniak and Dupont, “Is there an alternative to quality adjusted life years,” 354.

238 “Application in the Real World,” Innovation and Value Initiative, updated 2019, https://www.thevalueinitiative

.org/application-real-world/.

239 Beresniak and Dupont, “Is there an alternative to quality adjusted life years,” 354.

240 Innovation and Value Initiative, “Application in the Real World,” Praveen Thokala et al., “Multiple Criteria Decision 

Analysis for Health Care Decision Making—An Introduction: Report 1 of the ISPOR MCDA Emerging Good Practices 

Task Force,” Value in Health 19, no. 1 (2016): 1–13; Fifarma, “Multiple Criteria Decision Analysis for Healthcare 

Decision-Making,” http://www.fifarma.org/wp-content/uploads/2019/05/Fact-Sheet-Roche-ENG-FINAL.pdf.

241 “Application in the Real World,” Innovation and Value Initiative, updated 2019, https://www.thevalueinitiative

.org/application-real-world/.

242 “IVI-RA Value Tool,” Innovation and Value Initiative, http://apps.thevalueinitiative.org/ivi-ra/.

243 Beresniak and Dupont, “Is there an alternative to quality adjusted life years?” 354.

244 Beresniak and Dupont, “Is there an alternative to quality adjusted life years?” 354.

245 National Health Council, The Patient Voice in Value: The National Health Council Patient-Centered Value Model 

Rubric, March 2016, http://www.nationalhealthcouncil.org/sites/default/files/Value-Rubric.pdf, 2.

246 Partnership to Improve Patient Care, Uses and Misuses of the QALY, 18.

247 FasterCures, Patient Perspective Value Framework, Version 1.0. (Washington, DC: Avalere Health, May 2017), 

https://www.fastercures.org/assets/Uploads/PPVF-Version-1.0-Methodology-Report-Final.pdf.

248 FasterCures, Patient Perspective Value Framework, 8–9.

249 FasterCures, Patient Perspective Value Framework, 8–9.

250 FasterCures, Patient Perspective Value Framework, 34–35.

251 Faster Cures, Patient Perspective Value Framework, 15–19.

252 FasterCures, Patient Perspective Value Framework, 10.

253 Jalpa A. Doshi, Ellen Miller Sonet, Justin T. Puckett, and Henry Glick, “The Need for a New Patient Centered 

Decision Tool for Value-Based Treatment Choices in Oncology,” HealthAffairs (blog), Health Affairs, March 19, 

2018, https://www.healthaffairs.org/do/10.1377/hblog20180309.241877/full/.

254 Jason Shafrin, “The Efficiency Frontier in Health Economics,” Healthcare Economist (blog), June 9, 2014, 

https://www.healthcare-economist.com/2014/06/09/the-efficiency-frontier-in-health-economics/.

255 Will Kenton, “Efficient Frontier,” Investopedia, updated May 30, 2018, https://www.investopedia.com/terms/e/

efficientfrontier.asp.

256 Kenton, “Efficient Frontier.”

257 German Institute for Quality and Efficiency in Health Care, General Methods for the Assessment of the 

Relation of Benefits to Costs, Version 1.0, November 19, 2009, https://www.iqwig.de/download/General_

Methods_for_the_Assessment_of_the_Relation_of_Benefits_to_Costs.pdf, 32, fig. 5.

258 Shafrin, “The Efficiency Frontier in Health Economics.”

259 Issac Coro Ramos, Stefan K. Lhachimi, Andreas Gerber Grote, and Maiwenn J. Al, “Cost Recommendation 

Under Uncertainty in IQWiG’s Efficiency Frontier Framework,” Medical Decision Making 37 (2017): 162.

260 Coro Ramos et al., “Cost Recommendation Under Uncertainty,” 162–63.

261 Ari Ne’eman, interview with Kelly Israel, November 27, 2018.

262 German Institute for Quality and Efficiency in Health Care, General Methods for the Assessment of the 

Relation of Benefits to Costs, 4; German Institute for Quality and Efficiency in Health Care, Methods for 

Assessment of the Relation of Benefits to Costs in the German Statutory Health Care System, Version 1.1, 

September 10, 2008, https://www.iqwig.de/download/08-10-14_Draft_Methods_of_the_Relation_of_Benefits_

to_Costs_v_1_1.pdf, 13–15.

Quality-Adjusted Life Years and the Devaluation of Life with Disability 85
263 Axel C. Mühlbacher, Andrew Sadler, “The Probabilistic Efficiency Frontier: A Framework for Cost-Effectiveness 

Analysis in Germany Put into Practice for Hepatitis C Treatment Options,” Value in Health 20, no. 2 (2017): 266.

264 Beresniak and Dupont, “Is There an Alternative to Quality Adjusted Life Years?” 355; Gillett, “NHS Drugs, 

Aristotle, and Health Economics”; Jeremy Laurance, “The Cost of NHS Health Care: Deciding Who Lives 

and Who Dies,” Independent, March 9, 2015, https://www.independent.co.uk/life-style/health-and-families/

features/the-cost-of-nhs-health-care-deciding-who-lives-and-who-dies-10096784.html.

265 Beresniak and Dupont, “Is There an Alternative to Quality Adjusted Life Years?” 355–56.

266 Joe Stramondo, interview with Kelly Israel, November 21, 2018.

267 Ari Ne’eman, interview with Ana Torres Davis (NCD), January 9, 2019.

268 Steve Pearson, interview with Ana Torres Davis (NCD), February 1, 2019.

86 National Council on Disability
National Council on Disability 

1331 F Street, NW, Suite 850 

Washington, DC 20004