When we measure life through productivity, who gets left behind? Using PALYs in a global context
By Paige Boklaschuk and Cat Wang
We all have an intuition about how a disease would impact our life. But who decides how life is measured, and is it useful in answering global health questions?
Health-adjusted life years or HALYs attempt to summarize the complexity of disease burden into a single number. They can be useful to understand how a disease impacts society, but there are many considerations that should be made in a global health context.
There are two main HALYs used in public health, which focus on either quality of life or disability: QALYs (quality-adjusted life years) combine health quality of life with number of years lived, while DALYs (disability-adjusted life years) combine years of life lost due to a disease with the severity of disability. QALYs and DALYs measure two sides of the same coin. QALYs ask: “How good is life with this condition, and how long does it last?” while DALYs ask: “How bad is life with this condition, and how long does it last?”
Weighing up QALYs
A disability weight of 0 represents perfect health and 1.0 represents death. Most diseases fall somewhere in between. The specific disability weights for common conditions were assigned in the Global Burden of Disease study. The study determined weights from community surveys where people were presented with two disabilities and asked to determine which one they believed represented better health. Evaluations of the DALY weights have included a global sample from Bangladesh, Indonesia, Peru, Tanzania, and the USA. By analyzing the results across many surveys, disease weights could be established. For example, distance vision blindness is given a disability of 0.195.
These scores are useful, but far from perfect; disability weights are based on the assumptions of people who may not have lived experience of that disease. Further, by declaring that someone with no disabilities is at a ‘full score’, DALY measures can be ableist by implying that living without disease or disability is normal and anything otherwise is a ‘less complete’ experience of life. Indeed, a large portion of the world lives with medical conditions, and they should not be considered the exception to the rule. The actual experience of someone with a disease may be very different than what one would expect. Take as an example Michael May, who lived from age 3 to 45 without sight, until he was given the opportunity to regain his sight using stem-cell transplant surgery. Without vision, Michael broke records as a downhill skier, worked for the CIA, and was a successful inventor. While regaining his sight came with many positive experiences, it also caused a lot of frustration as he was unable to regain the normal brain function associated with interpreting 3D stimuli and facial recognition. The actual ‘weight’ of disability versus ‘regained health’ is much harder to quantify when individual experiences can vary so greatly. Furthermore, the cultural interpretation, treatment options, and stigma associated with disabilities varies globally.
Despite these limitations, QALYs and DALYs are useful metrics for decision making in global health. They may help physicians and public health workers make decisions based on the cost-effectiveness of interventions. They can also be useful for estimating burdens of disease and comparing them between countries or allocating research and healthcare resources to make the biggest impact.
In comes a new measure: The PALY
A new QALY measure has emerged in the research world: the productivity-adjusted life year (PALY), which requires extra consideration for use in a global health context. Many diseases can cause people to miss work or stop working earlier than a normal retirement age. The PALY captures this by using a value of 0 as complete unproductivity and 1.0 as complete productivity. Complete productivity would be the expected level of productivity for a person with no disease. PALYs have been used to characterize various global health conditions. For example, they’ve been used as a tool to understand the impact of hypertension in different health facilities in Zambia and to advocate for better adherence to antihypertensive drugs in certain Zambian populations. They are useful because they highlight the potential for societal gains in productivity with progress in treatment. As PALYs become more popular, and if they gain the interest of politicians, it will be important to ask whether it is useful or ethical to measure disease based on productivity.
PALYs have some important strengths. First, they measure loss of time spent at work, which is objective, and may be easier to compare between countries. This is unlike the quality or disability measures used for QALYs and DALYs, which are based on subjective perception of disease, and which can vary vastly between populations. They can also be used to advocate for those with rare diseases. For instance, PALYs can be used to vouch for the importance of investing in research to treat rare cancers. Even though they do not affect many people, rare cancers can have a large economic impact. Similarly, PALYs may be useful in a global health context to advocate for under-resourced and highly cost-effective interventions such as lead poisoning prevention. And with climate change-related disasters being most likely to affect vulnerably countries, PALYs may be an important tool to build awareness about the global disparities in lost productivity due to climate change-related disasters and health risks.
Productivity by proxy measure
PALYs are a useful tool but do not capture fine details; they are more like a paint roller than a brush. In their attempt to capture productivity changes in people with a disease, they might miss the lost productivity of caretakers missing work to spend time with that person. These measures are likely to vary in global contexts due to disparities in healthcare access. They also only incorporate data from people doing paid labor, which means that productivity losses from people such as stay-at-home parents are not included in the measurement. Again, distributions of unrecognized and unpaid labor are likely to vary globally. PALYs also only measure people during ‘working ages’, which is usually defined as 16-65. This is a problem because if PALYs are to be used to decide where to budget healthcare dollars, then the needs of people outside the working age may be neglected. Furthermore, different studies have different definitions of ‘working ages’, which is an important consideration in study design using PALYs. For instance, one study quantified the economic impact of diabetes in Bangladesh using working ages of 20-59, despite the fact that child labor is extremely prevalent in Bangladesh.
PALYs only measure time at work lost, not the complexity of individual experiences. Loss of productivity from a disease will not affect each person the same way. Cultural, economic, and age groups have different definitions and preferences around health. There are also different levels of productivity loss for a disease in different locations. Recall Michael May, who lived a vibrant life with blindness. Blindness, for example, would pose a significant barrier to productivity in a society that mainly engages in physical labor and has less access to healthcare.
It is important to remember that measures of disease on a population level should be used alongside the voices of people living with the disease. Access to healthcare, working culture norms, and unpaid labor vary globally. These factors must all be considered when interpreting PALYs in global health. There are also ethical implications with justifying a global health intervention solely on the basis of increasing productivity, especially if the beneficiaries are from another nation. People living with a disease should know that their value is not encapsulated simply by the amount of work they miss.
Paige Boklaschuk (left) is a Master of Science Epidemiology candidate at McGill University. Her thesis explores exercise patterns and ovarian cancer.
Cat Wang (right) holds a Master of Science in Public Health from McGill University. She is a science communicator at the McGill Office for Science and Society.