HTAi 2026 Insights: PALYs and PALE as Measures of Productivity Losses

HTAi is a leading platform for the global health technology assessment (HTA) community, bringing together researchers, policymakers, patients, industry and healthcare leaders to exchange ideas, share evidence and explore how HTA can address the challenges facing health systems across borders and levels of system maturity. The theme of HTAi’s 2026 Annual Meeting, HTA as a System Shaper, highlights the evolving role of health technology assessment beyond evaluating individual technologies to actively informing governance, prioritisation, equity, sustainability and the long-term resilience of healthcare systems.

A central topic at the conference was the consideration of productivity in Health Technology Assessment and cost-effectiveness analyses. Productivity measurement in health economics helps quantify the extent to which health technologies generate productivity gains across the population, including improved workforce participation and reductions in both absenteeism and presenteeism. Productivity is typically considered in economic models when costs and effects are measured from the societal perspective, most commonly by incorporating productivity losses as indirect costs alongside healthcare costs.¹

What are PALYs and PALE?

Although the societal perspective is referenced in HTA methods guides across many countries, there remains variation in how it is defined and applied and limited guidance on how productivity should be captured.² An alternative approach is to measure productivity as an outcome instead of costs: productivity-adjusted life years (PALYs) as an analogue to quality-adjusted life years (QALYs), and productivity-adjusted life expectancy (PALE) as an analogue to quality-adjusted life expectancy (QALE). ³ But some key questions arise: How are PALYs and PALE estimated? What do they show? Are they a useful tool for measuring productivity losses?

How are PALYs and PALE calculated?

The starting point for measuring PALYs is a productivity index, defined as the actual number of working hours divided by the typical number of working hours, ranging from 0 (completely unproductive) to 1 (completely productive).⁴ PALYs are then calculated by multiplying the productivity index by years lived, thereby quantifying the impact of a disease or intervention on work productivity.

PALE extends the concept of PALYs to a population baseline: combined with life tables, it estimates the number of productive years a population can expect at each age, against which disease-specific productivity burdens can be benchmarked.

Australian data show how PALYs can quantify disease burden

Examples of how population norms for the productivity index, and subsequently PALE, can be calculated were presented in two oral presentations at HTAi 2026 (OS02 – New Frontiers in HTA Methods: Elicitation, Digital Frameworks, and Productivity Measurement).

Using data from the Household, Income and Labour Dynamics in Australia (HILDA) Survey, a nationally representative annual panel survey, presenteeism (reduced performance whilst working) and absenteeism (sick leave days) were used to calculate productivity indices for employed (paid and unpaid work) and non-employed (unpaid work only) individuals, which were then averaged to a population-level index. Panellists cited an overall population productivity index of 0.831, indicating that Australians operate at approximately 83% of their full productive capacity when accounting for both paid and unpaid work.^4,5 Notably, males (0.847) scored higher than females (0.815), reflecting that women spend more time in unpaid work and therefore bear a disproportionately higher productivity burden when ill.^4,5

The researchers illustrated this metric using obstructive sleep apnoea: a lifetime modelling study estimated that a 10% reduction in OSA prevalence and associated comorbidities would result in 150,950 PALYs compared with only 109,626 QALYs. This suggests that sleep apnoea impairs the ability to work more severely than it impairs quality of life, an effect that would be largely disregarded in a conventional QALY-based analysis.^6,7

How does measuring productivity as an outcome change our understanding of disease burden?

Taken together, these findings suggest that measuring productivity as an outcome can provide a more comprehensive and equitable picture of disease burden, particularly for groups such as women and retirees who are primarily engaged in unpaid work and whose contributions are overlooked when productivity is valued through paid earnings alone.^4,6

PALYs can also be translated into monetary terms (for example, via gross domestic product per full-time equivalent worker) to communicate the economic case for prevention to policymakers. With the emergence of population norms and PALE, they can provide a consistent baseline for comparing productivity losses across diseases and settings.⁸

The challenges of using PALYs and PALE in HTA decision-making

There are several key challenges in the current landscape that stand in the way of uptake across health economics. There is currently no established willingness-to-pay threshold for a PALY, which limits their direct use in decision-making. There is also a risk of double counting if productivity effects are included both within PALYs as an outcome and as indirect costs within the same analysis. In addition, estimates of PALYs and PALE rely on the construction of productivity indices, for which methods can vary, highlighting the need for greater standardisation to ensure comparability across studies.⁸

Are PALYs and PALE the future of measuring productivity losses?

The discussions at HTAi 2026 suggest that PALYs and PALE are a promising addition to the health economist’s toolkit, highlighting societal consequences of disease beyond counting indirect costs alone. Yet their routine use in HTA will depend on the development of standardised methodological guidance, availability of data to estimate productivity indices and the willingness of HTA bodies to broaden their evaluation perspective. Until then, PALYs and PALE remain supplementary analyses: not yet a way forward for HTA decision-making itself but a compelling way of measuring productivity losses.