When evaluating the economic burden of disease, productivity loss is an important part of the equation. But are we capturing all of it?
Traditional approaches often rely on administrative data such as sick leave and disability. These measures tell us when patients are absent from work — but they can miss what happens when patients continue working while their health affects their ability to perform at their usual capacity.
This less visible burden, known as presenteeism, can be particularly relevant for people living with chronic or fluctuating conditions. Fatigue, pain, cognitive difficulties or disease flares may affect productivity without necessarily resulting in a day off work.
And the impact can extend even further.
Reduced working hours, career interruptions, delayed education or changes in professional roles can all contribute to the broader economic burden of disease — yet these consequences may be difficult to capture through medico-administrative databases alone.
When patient-reported data can make the difference
Patient-reported data can complement traditional sources by providing a more granular picture of how disease affects patients’ professional and daily lives.
They can help researchers capture not only absenteeism, but also:
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- Presenteeism and overall work impairment
- Functional limitations while working
- Changes in employment or working hours
- Variations in productivity over time
- Longer-term impacts on education, career and family decisions
This becomes particularly important in chronic and fluctuating conditions, rare diseases, early-onset diseases and populations for which traditional data sources may be limited or fragmented.
From productivity loss to economic burden
Capturing these experiences is only the first step.
Which instruments should researchers use? How can patient-reported productivity loss be translated into economic costs? And how can methodological choices affect the results of an HEOR model?
The answers matter because productivity loss is not a single concept. What researchers measure, the data they use and how they assign an economic value to that loss can lead to very different estimates of disease burden.
Our whitepaper, “When, how and why should we assess productivity loss using patient-reported data?”, explores these questions in more detail, including:
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- When patient-reported data are particularly valuable for cost modelling
- The instruments available to measure productivity loss
- Approaches for translating productivity impairment into economic costs
- The limitations researchers should consider
- Why these methodological choices matter for HEOR models
Want to explore the methodology?
Download the full infographic to discover when and how patient-reported data can strengthen productivity-loss assessment in HEOR.
