Demonstration of quality-adjusted life years (QALYs) for two individuals. Individual A (who did not receive an intervention) has fewer QALYs than individual B (who received an intervention). The letters A and B designate the boundary lines, with the QALY for A being only the blue area, the QALY for B being the blue area plus the additional tan area. NB It is possible to experience an improvement in health-related quality of life with age, for example through healthier life choices.
The quality-adjusted life year (QALY) is a generic measure of disease burden, including both the quality and the quantity of life lived.[1][2] It is used in economic evaluation to assess the value of medical interventions.[1] One QALY equates to one year in perfect health.[2] QALY scores range from 1 (perfect health) to 0 (dead).[3] QALYs can be used to inform health insurance coverage determinations, treatment decisions, to evaluate programs, and to set priorities for future programs.[3]
Critics argue that the QALY oversimplifies how actual patients would assess risks and outcomes, and that its use may restrict patients with disabilities from accessing treatment.[4] Proponents of the measure acknowledge that the QALY has some shortcomings, but that its ability to quantify tradeoffs and opportunity costs from the patient, and societal perspective make it a critical tool for equitably allocating resources.[4]
Calculation
A measure of the state of health of a person or group in which the benefits, in terms of length of life, are adjusted to reflect the quality of life. One quality-adjusted life year (QALY) is equal to 1 year of life in perfect health.[2] It combines two different benefits of treatment—length of life and quality of life—into a single number that can be compared across different types of treatments. For example, one year lived in perfect health equates to 1 QALY. This can be interpreted as a person getting 100% of the value for that year. A year lived in a less than perfect state of health can also be expressed as the amount of value accrued to the person living it. For example, 1 year of life lived in a situation with utility 0.5 yields 0.5 QALYs—a person experiencing this state is getting only 50% of the possible value of that year. In other words, they value the experience of being in less than perfect health for a full year as much as they value living for half a year in perfect health (0.5 years × 1 Utility).[5]
Therefore, calculating a QALY requires two inputs. One is the utility value (or utility weight) associated with a given state of health by the years lived in that state. The underlying measure of utility is derived from clinical trials, and studies that measure how people feel in these specific states of health. The way they feel in a state of perfect health equates to a value of 1 (or 100%). Death is assigned a utility of 0 (or 0%), and in some circumstances it is possible to accrue negative QALYs to reflect health states deemed "worse than dead."[3] The value people perceive in less than perfect states of health are expressed as a fraction between 0 and 1.
The second input is the amount of time people live in various states of health. This information usually comes from clinical trials.
The QALY calculation is simple: the change in utility value induced by the treatment is multiplied by the duration of the treatment effect to provide the number of QALYs gained. QALYs can then be incorporated with medical costs to arrive at a final common denominator of cost/QALY. This parameter can be used to compare the cost-effectiveness of any treatment.[5]
Weighting
The utility values used in QALY calculations are generally determined by methods that measure people's willingness to trade time in different health states, such as those proposed in the Journal of Health Economics:[6]
Time-trade-off (TTO): Respondents are asked to choose between remaining in a state of ill health for a period of time, or being restored to perfect health but having a shorter life expectancy.
Standard gamble (SG): Respondents are asked to choose between remaining in a state of ill health for a period of time, or choosing a medical intervention which has a chance of either restoring them to perfect health or killing them.
Visual analogue scale (VAS): Respondents are asked to rate a state of ill health on a scale from 0 to 100, with 0 representing being dead, and 100 representing perfect health. This method has the advantage of being the easiest to ask, but is the most subjective.
Another way of determining the weight associated with a particular health state is to use standard descriptive systems such as the EuroQol Group's EQ-5D questionnaire, which categorizes health states according to five dimensions: mobility, self-care, usual activities (e.g. work, study, homework or leisure activities), pain/discomfort and anxiety/depression.[7]
In 1989, the state of Oregon attempted to reform its Medicaid system by incorporating the QALY metric. This was found to be discriminatory, and in violation of the Americans with Disabilities Act in 1992.[10]Louis W. Sullivan, the Secretary of Health and Human Services at the time, criticized the plan by stating that "Oregon's plan in substantial part values the life of a person with a disability less than the life of a person without a disability."[11]
History
The first mention of Quality Adjusted Life Years appeared in a doctoral thesis at Harvard University by Joseph S. Pliskin (1974). The need to consider quality of life is credited to work by Klarman et al. (1968),[12] Fanshel and Bush (1970) [13] and Torrance et al. (1972) [14] who suggested the idea of length of life adjusted by indices of functionality or health.[15] A 1976 article by Zeckhauser and Shepard[16] was the first appearance in print of the term.[17] QALYs were later promoted through medical technology assessments conducted by the US CongressOffice of Technology Assessment.
In 1980, Pliskin et al. justified the QALY indicator using multiattribute utility theory: if a set of conditions pertaining to agent preferences on life years and quality of life are verified, then it is possible to express the agent's preferences about couples (number of life years/health state), by an interval (Neumannian) utility function.[18] This utility function would be equal to the product of an interval utility function on "life years", and an interval utility function on "health state".
According to Pliskin et al., the QALY model requires utility independent, risk neutral, and constant proportional tradeoff behavior.[18] For the more general case of a life time health profile (i.e., experiencing more than one health state during the remaining years of life), the utility of a life time health profile must equal the sum of single-period utilities.[19] Because of these theoretical assumptions, the meaning and usefulness of the QALY is debated.[5][20][21] Perfect health is difficult, if not impossible, to define. Some argue that there are health states worse than being dead, and that therefore there should be negative values possible on the health spectrum (indeed, some health economists have incorporated negative values into calculations). Determining the level of health depends on measures that some argue place disproportionate importance on physical pain or disability over mental health.[22]
The method of ranking interventions on grounds of their cost per QALY gained ratio (or ICER) is controversial because it implies a quasi-utilitarian calculus to determine who will or will not receive treatment.[23] However, its supporters argue that since health care resources are inevitably limited, this method enables them to be allocated in the way that is approximately optimal for society, including most patients. Another concern is that it does not take into account equity issues such as the overall distribution of health states—particularly since younger, healthier cohorts have many times more QALYs than older or sicker individuals. As a result, QALY analysis may undervalue treatments which benefit the elderly or others with a lower life expectancy. Also, many would argue that all else being equal, patients with more severe illness should be prioritized over patients with less severe illness if both would get the same absolute increase in utility.[24]
As early as 1989, Loomes and McKenzie recommended that research be conducted concerning the validity of QALYs.[25] In 2010, with funding from the European Commission, the European Consortium in Healthcare Outcomes and Cost-Benefit Research (ECHOUTCOME) began a major study on QALYs as used in health technology assessment.[26]Ariel Beresniak, the study's lead author, was quoted as saying that it was the "largest-ever study specifically dedicated to testing the assumptions of the QALY."[27] In January 2013, at its final conference, ECHOUTCOME released preliminary results of its study which surveyed 1361 people "from academia" in Belgium, France, Italy and the UK.[27][28][29] The researchers asked the subjects to respond to 14 questions concerning their preferences for various health states and durations of those states (e.g., 15 years limping versus 5 years in a wheelchair).[29] They concluded that:
"Preferences expressed by the respondents were not consistent with the QALY theoretical assumptions";
Quality of life can be measured in consistent intervals;
Life-years and quality of life are independent of each other;
People are neutral about risk; and
Willingness to gain or lose life-years is constant over time.[29]
ECHOUTCOME also released "European Guidelines for Cost-Effectiveness Assessments of Health Technologies", which recommended not using QALYs in healthcare decision making.[30] Instead, the guidelines recommended that cost-effectiveness analyses focus on "costs per relevant clinical outcome."[27][30]
Third, problems with QALYs were already widely acknowledged.[28]
Fourth, the researchers did not take budgetary constraints into consideration.[28]
Fifth, the UK's National Institute for Health and Care Excellence uses QALYs that are based on 3395 interviews with residents of the UK, as opposed to residents of several European countries.[27]
Finally, according to Franco Sassi, a senior health economist at the Organization for Economic Co-operation and Development, people who call for the elimination of QALYs may have "vested interests".[27]
While supporters laud QALY's efficiency, critics argue that use of QALY can cause medical inefficiencies because a less-effective, cheaper drug may be approved based on its QALY calculation.[31]
The use of QALYs has been criticized by disability advocates because otherwise healthy individuals cannot return to full health or achieve a high QALY score. Treatments for quadriplegics, patients with multiple sclerosis, or other disabilities are valued less under a QALY-based system.[32]
Critics also argue that a QALY-based system would limit research on treatments for rare disorders because the upfront costs of the treatments tend to be higher. Officials in the United Kingdom were forced to create the Cancer Drugs Fund to pay for new drugs regardless of their QALY rating because innovation had stalled since NICE was founded. At the time, one in seven drugs were turned down.[33] Additionally there is a trend where QALY is getting position as a capital allocation tool although many sources and publications show that QALY has relatively significant gaps as formula and as organization management mechanism in healthcare[34]
The Partnership to Improve Patient Care, a group opposed to the adoption of QALY-based metrics, argued that a QALY-based system could exacerbate racial disparities in medicine because there is no consideration of genetic background, demographics, or comorbidities that may be elevated in minority racial groups that do not have as much weight in the consideration of the average year of perfect health.[35]
Critics have also noted that QALY only considers the quality of life when patients may choose to suffer negative side-effects to live long enough to attend a milestone event, such as a wedding or graduation.[31]
The Rule of rescue and immoral or "inhuman acting" are frequently used arguments to ignore cost-effectiveness analysis and the use of QALYs. Especially during the 2020/2021 Covid-19 pandemic, national responses represented a massive form of applying the 'rule of rescue' and disregard of cost-effectiveness analysis (see e.g. Utilitarianism and the pandemic).
Both the Rule of rescue and immoral behavior are heavily attacked by Shepley Orr and Jonathan Wolff in their 2014 article "Reconciling cost-effectiveness with the rule of rescue: the institutional division of moral labor".[36] They argued that the "Rule of rescue" is the result of wrong reasoning, and that cost-effectiveness reasoning with the aid of QALYs always leads to moral superior outcomes and optimal public health outcome, although not always perfect, given constraints of resources.
Future development
The UK Medical Research Council and others are exploring improvements to or replacements for QALYs.[37] Among other possibilities are extending the data used to calculate QALYs (e.g., by using different survey instruments); "using well-being to value outcomes" (e.g., by developing a "well-being-adjusted life-year"; and by value outcomes in monetary terms.[37] In 2018 HM Treasury set a discount rate of 1.5% for QALYs, which is lower than the discount rates for other costs and benefits, because the QALY is a direct utility measure.[38]
Cost-effectiveness analysis (CEA) is a form of economic analysis that compares the relative costs and outcomes (effects) of different courses of action. Cost-effectiveness analysis is distinct from cost–benefit analysis, which assigns a monetary value to the measure of effect. Cost-effectiveness analysis is often used in the field of health services, where it may be inappropriate to monetize health effect. Typically the CEA is expressed in terms of a ratio where the denominator is a gain in health from a measure and the numerator is the cost associated with the health gain. The most commonly used outcome measure is quality-adjusted life years (QALY).
The incremental cost-effectiveness ratio (ICER) is a statistic used in cost-effectiveness analysis to summarise the cost-effectiveness of a health care intervention. It is defined by the difference in cost between two possible interventions, divided by the difference in their effect. It represents the average incremental cost associated with 1 additional unit of the measure of effect. The ICER can be estimated as:
Health economics is a branch of economics concerned with issues related to efficiency, effectiveness, value and behavior in the production and consumption of health and healthcare. Health economics is important in determining how to improve health outcomes and lifestyle patterns through interactions between individuals, healthcare providers and clinical settings. In broad terms, health economists study the functioning of healthcare systems and health-affecting behaviors such as smoking, diabetes, and obesity.
Utilitarian bioethics refers to the branch of bioethics that incorporates principles of utilitarianism to directing practices and resources where they will have the most usefulness and highest likelihood to produce happiness, in regards to medicine, health, and medical or biological research.
The National Institute for Health and Care Excellence (NICE) is an executive non-departmental public body of the Department of Health and Social Care.
Preventive healthcare, or prophylaxis, is the application of healthcare measures to prevent diseases. Disease and disability are affected by environmental factors, genetic predisposition, disease agents, and lifestyle choices, and are dynamic processes that begin before individuals realize they are affected. Disease prevention relies on anticipatory actions that can be categorized as primal, primary, secondary, and tertiary prevention.
Cost–utility analysis (CUA) is a form of economic analysis used to guide procurement decisions. The most common and well-known application of this analysis is in pharmacoeconomics, especially health technology assessment (HTA).
Disability-adjusted life years (DALYs) are a measure of overall disease burden, expressed as the number of years lost due to ill-health, disability, or early death. It was developed in the 1990s as a way of comparing the overall health and life expectancy of different countries.
Pharmacoeconomics refers to the scientific discipline that compares the value of one pharmaceutical drug or drug therapy to another. It is a sub-discipline of health economics. A pharmacoeconomic study evaluates the cost and effects of a pharmaceutical product. Pharmacoeconomic studies serve to guide optimal healthcare resource allocation, in a standardized and scientifically grounded manner.
A patient-reported outcome (PRO) is a health outcome directly reported by the patient who experienced it. It stands in contrast to an outcome reported by someone else, such as a physician-reported outcome, a nurse-reported outcome, and so on. PRO methods, such as questionnaires, are used in clinical trials or other clinical settings, to help better understand a treatment's efficacy or effectiveness. The use of digitized PROs, or electronic patient-reported outcomes (ePROs), is on the rise in today's health research setting.
The Short Form (36) Health Survey is a 36-item, patient-reported survey of patient health. The SF-36 is a measure of health status and an abbreviated variant of it, the SF-6D, is commonly used in health economics as a variable in the quality-adjusted life year calculation to determine the cost-effectiveness of a health treatment. The SF-36 is also commonly utilized in health psychology research to examine the burden of disease. The original SF-36 stemmed from the Medical Outcome Study, MOS, which was conducted by the RAND Corporation. Since then a group of researchers from the original study released a commercial version of SF-36 while the original SF-36 is available in public domain license free from RAND. A shorter version is the SF-12, which contains 12 items rather than 36. If having only adequate physical and mental health summary scores is of interest, "then the SF12 may be the instrument of choice".
Outcomes research is a branch of public health research which studies the end results of the structure and processes of the health care system on the health and well-being of patients and populations. According to one medical outcomes and guidelines source book - 1996, Outcomes research includes health services research that focuses on identifying variations in medical procedures and associated health outcomes. Though listed as a synonym for the National Library of Medicine MeSH term "Outcome Assessment ", outcomes research may refer to both health services research and healthcare outcomes assessment, which aims at health technology assessment, decision making, and policy analysis through systematic evaluation of quality of care, access, and effectiveness.
In general, quality of life is the perceived quality of an individual's daily life, that is, an assessment of their well-being or lack thereof. This includes all emotional, social and physical aspects of the individual's life. In health care, health-related quality of life (HRQoL) is an assessment of how the individual's well-being may be affected over time by a disease, disability or disorder.
Comparative effectiveness research (CER) is the direct comparison of existing health care interventions to determine which work best for which patients and which pose the greatest benefits and harms. The core question of comparative effectiveness research is which treatment works best, for whom, and under what circumstances. Engaging various stakeholders in this process, while difficult, makes research more applicable through providing information that improves patient decision making.
Health care quality is a level of value provided by any health care resource, as determined by some measurement. As with quality in other fields, it is an assessment of whether something is good enough and whether it is suitable for its purpose. The goal of health care is to provide medical resources of high quality to all who need them; that is, to ensure good quality of life, cure illnesses when possible, to extend life expectancy, and so on. Researchers use a variety of quality measures to attempt to determine health care quality, including counts of a therapy's reduction or lessening of diseases identified by medical diagnosis, a decrease in the number of risk factors which people have following preventive care, or a survey of health indicators in a population who are accessing certain kinds of care.
The Health Utilities Index (HUI) is a rating scale used to measure general health status and health-related quality of life (HRQoL). HUI questionnaires are designed to map onto two classification systems, HUI-2 and HUI-3, capable of measuring 24,000 and 972,000 unique health states, respectively. HUI classifications measure a range of health domains with examples including sensation, mobility, pain, cognition, ambulation, and emotion. Health utility values are commonly produced using HUI as a component of the quality-adjusted life years (QALY) calculation used in population health and economics.
The Institute for Clinical and Economic Review (ICER) is a Boston-based independent nonprofit organization that seeks to place a value on medical care by providing comprehensive clinical and cost-effectiveness analyses of treatments, tests, and procedures.
ISPOR—The Professional Society for Health Economics and Outcomes Research, also known as ISPOR is a global, nonprofit 501(c)(3) public organization for educational and scientific purposes, as defined by the United States Internal Revenue Service.
The Equal Value of Life Years Gained or evLYG is a generic measure used to determine how much a medical treatment can extend the life of the patient. Unlike other healthcare metrics, the evLYG does not consider the quality of life for the patient; it exclusively considers the length of life. It is used in economic evaluation to determine the added time a treatment may give a patient. Critics argue the evLYG measurement is flawed because it values a medication based solely on the added years of life. A higher priced drug that both extends life and adds two years of life receives the same evLYG score as a lower priced drug that adds two years but does not improve life.
Donald L. Patrick is a social scientist, academic, and an author. He is a Professor Emeritus of Health Systems and Population Health at the University of Washington, Director of Seattle Quality of Life Group, and Creator of the Biobehavioral Cancer Prevention and Control Training Program jointly with the Fred Hutchinson Cancer Center. He has served as the co-chair of the Cochrane Collaboration's Patient Reported Outcomes Methods Group. His research interests revolve around various aspects of public health which integrate the themes from fields such as psychological intervention, social stratification, public health, and quality of life. Much of his research works have focused on outcomes research on vulnerable populations, health disparities, and end-of-life-care.
↑ Torrance, George E. (1986). "Measurement of health state utilities for economic appraisal: A review". Journal of Health Economics. 5 (1): 1–30. doi:10.1016/0167-6296(86)90020-2. PMID10311607.
↑ Weinstein, Milton; Zeckhauser, Richard (1973-04-01). "Critical ratios and efficient allocation". Journal of Public Economics. 2 (2): 147–157. doi:10.1016/0047-2727(73)90002-9.
↑ Klarman, Herbert E.; Francis, John O'S; Rosenthal, Gerald D. (1968). "Cost effectiveness analysis applied to the treatment of chronic renal disease". Medical Care. 6 (1): 48–54. doi:10.1097/00005650-196801000-00005. S2CID72031480.
1 2 Pliskin, J. S.; Shepard, D. S.; Weinstein, M. C. (1980). "Utility Functions for Life Years and Health Status". Operations Research. 28 (1): 206–24. doi:10.1287/opre.28.1.206. JSTOR172147.
↑ Mehrez, A; Gafni, A (April 1991). "The healthy-years equivalents: how to measure them using the standard gamble approach". Medical Decision Making. 11 (2): 140–6. doi:10.1177/0272989X9101100212. PMID1865782. S2CID20873927.
↑ Mortimer, D.; Segal, L. (2007). "Comparing the Incomparable? A Systematic Review of Competing Techniques for Converting Descriptive Measures of Health Status into QALY-Weights". Medical Decision Making. 28 (1): 66–89. doi:10.1177/0272989X07309642. PMID18263562. S2CID40830765.
↑ Gandjour, A; Gafni, A (March 2010). "The additive utility assumption of the QALY model revisited". Journal of Health Economics. 29 (2): 325–8, author reply 329–31. doi:10.1016/j.jhealeco.2009.11.001. PMID20004033.
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