Do Productivity Costs Matter?

Krol, Marieke; Papenburg, Jocé; Koopmanschap, Marc; Brouwer, Werner

doi:10.2165/11539970-000000000-00000

Cited by 107 publications

(60 citation statements)

References 121 publications

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“…In particular they could help form a picture of the reduction in the economic burden that may be achieved by implementation of particular primary, secondary or tertiary prevention strategies. As previous research has noted failure to include these costs in decision-making leads to an underestimation of societal costs and may lead to welfare damaging decisions [26]. Estimates of productivity losses may also be important sources of data for economic evaluations of specific health technologies.…”

Section: Discussionmentioning

confidence: 99%

“…Estimates of productivity losses may also be important sources of data for economic evaluations of specific health technologies. Some leading expert panels (for example the US Panel on Cost-Effectiveness in Health and Medicine [27]) and economic textbooks and advocate a societal perspective for economic evaluations but, in reality, relatively few evaluations include productivity costs [26], perhaps due to a lack of available data (in some instances, at least). Moreover, combined with direct medical costs and direct non-medical costs (including patient time, travel and out-of-pocket costs), such estimates provide an important - yet rarely quantified - building block in constructing an accurate measure of the total economic burden of cancer on society.…”

Section: Discussionmentioning

confidence: 99%

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The cost of lost productivity due to premature cancer-related mortality: an economic measure of the cancer burden

Hanly

Sharp

2014

BMC Cancer

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BackgroundMost measures of the cancer burden take a public health perspective. Cancer also has a significant economic impact on society. To assess this economic burden, we estimated years of potential productive life lost (YPPLL) and costs of lost productivity due to premature cancer-related mortality in Ireland.MethodsAll cancers combined and the 10 sites accounting for most deaths in men and in women were considered. To compute YPPLL, deaths in 5-year age-bands between 15 and 64 years were multiplied by average working-life expectancy. Valuation of costs, using the human capital approach, involved multiplying YPPLL by age-and-gender specific gross wages, and adjusting for unemployment and workforce participation. Sensitivity analyses were conducted around retirement age and wage growth, labour force participation, employment and discount rates, and to explore the impact of including household production and caring costs. Costs were expressed in €2009.ResultsTotal YPPLL was lower in men than women (men = 10,873; women = 12,119). Premature cancer-related mortality costs were higher in men (men: total cost = €332 million, cost/death = €290,172, cost/YPPLL = €30,558; women: total cost = €177 million, cost/death = €159,959, cost/YPPLL = €14,628). Lung cancer had the highest premature mortality cost (€84.0 million; 16.5% of total costs), followed by cancers of the colorectum (€49.6 million; 9.7%), breast (€49.4 million; 9.7%) and brain & CNS (€42.4 million: 8.3%). The total economic cost of premature cancer-related mortality in Ireland amounted to €509.5 million or 0.3% of gross domestic product. An increase of one year in the retirement age increased the total all-cancer premature mortality cost by 9.9% for men and 5.9% for women. The inclusion of household production and caring costs increased the total cost to €945.7 million.ConclusionLost productivity costs due to cancer-related premature mortality are significant. The higher premature mortality cost in males than females reflects higher wages and rates of workforce participation. Productivity costs provide an alternative perspective on the cancer burden on society and may inform cancer control policy decisions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The cost of lost productivity due to premature cancer-related mortality: an economic measure of the cancer burden

Hanly

Sharp

2014

BMC Cancer

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“…The inclusion of productivity losses in such analyses would have a significant influence on determinations of cost-effectiveness, leading to different resource allocation decisions. Krol et al find that accounting for productivity costs can either increase or decrease the incremental cost-effectiveness ratio (ICER) between treatment arms [3, 4]. Thus, cost-effectiveness studies that account for productivity losses are useful in identifying interventions with a potentially broad impact, and do not necessarily lower the ICERs of an intervention.…”

Section: Introductionmentioning

confidence: 99%

“…Despite robust arguments in favour of including productivity loss in evaluation studies [3–6], current methods to value productivity loss are limited. Existing methods usually quantify productivity loss using wages as a proxy for marginal productivity [1, 7, 8].…”

Section: Introductionmentioning

confidence: 99%

Valuing productivity loss due to absenteeism: firm-level evidence from a Canadian linked employer-employee survey

et al. 2017

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In health economic evaluation studies, to value productivity loss due to absenteeism, existing methods use wages as a proxy value for marginal productivity. This study is the first to test the equality between wage and marginal productivity losses due to absenteeism separately for team workers and non-team workers. Our estimates are based on linked employer-employee data from Canada. Results indicate that team workers are more productive and earn higher wages than non-team workers. However, the productivity gap between these two groups is considerably larger than the wage gap. In small firms, employee absenteeism results in lower productivity and wages, and the marginal productivity loss due to team worker absenteeism is significantly higher than the wage loss. No similar wage-productivity gap exists for large firms. Our findings suggest that productivity loss or gain is most likely to be underestimated when valued according to wages for team workers. The findings help to value the burden of illness-related absenteeism. This is important for economic evaluations that seek to measure the productivity gain or loss of a health care technology or intervention, which in turn can impact policy makers’ funding decisions.Electronic supplementary materialThe online version of this article (doi:10.1186/s13561-016-0138-y) contains supplementary material, which is available to authorized users.

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“…While average wages are often easier to identify in the public domain, they do not reflect the established life cycle of wages which is better reflected using age-specific wage rates. The wage life cycle was established in human capital economic theory since workers usually start their career with low wages, see an increase as they gain more experience and expertise, and finally usually see a decrease in wages as they often begin working less in old age, and their employers are less incentivized to invest in older employees [17]. Due to the consistency and significance of the variance of earnings over a lifetime, age-specific wages are able to capture lifetime earnings projections more accurately.…”

Section: Introductionmentioning

confidence: 99%

A comparison of average wages with age-specific wages for assessing indirect productivity losses: analytic simplicity versus analytic precision

Connolly

Tashjian²,

Kotsopoulos³

et al. 2016

Eur J Health Econ

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ObjectivesNumerous approaches are used to estimate indirect productivity losses using various wage estimates applied to poor health in working aged adults. Considering the different wage estimation approaches observed in the published literature, we sought to assess variation in productivity loss estimates when using average wages compared with age-specific wages.MethodsPublished estimates for average and age-specific wages for combined male/female wages were obtained from the UK Office of National Statistics. A polynomial interpolation was used to convert 5-year age-banded wage data into annual age-specific wages estimates. To compare indirect cost estimates, average wages and age-specific wages were used to project productivity losses at various stages of life based on the human capital approach. Discount rates of 0, 3, and 6 % were applied to projected age-specific and average wage losses.ResultsUsing average wages was found to overestimate lifetime wages in conditions afflicting those aged 1–27 and 57–67, while underestimating lifetime wages in those aged 27–57. The difference was most significant for children where average wage overestimated wages by 15 % and for 40-year-olds where it underestimated wages by 14 %.ConclusionsLarge differences in projecting productivity losses exist when using the average wage applied over a lifetime. Specifically, use of average wages overestimates productivity losses between 8 and 15 % for childhood illnesses. Furthermore, during prime working years, use of average wages will underestimate productivity losses by 14 %. We suggest that to achieve more precise estimates of productivity losses, age-specific wages should become the standard analytic approach.

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Do Productivity Costs Matter?

Cited by 107 publications

References 121 publications

The cost of lost productivity due to premature cancer-related mortality: an economic measure of the cancer burden

The cost of lost productivity due to premature cancer-related mortality: an economic measure of the cancer burden

Valuing productivity loss due to absenteeism: firm-level evidence from a Canadian linked employer-employee survey

A comparison of average wages with age-specific wages for assessing indirect productivity losses: analytic simplicity versus analytic precision

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