M. Koopmanschap et al.
These studies have demonstrated the importance of considering productivity costs in economic evaluations of provisions of (occupational)
health care, such as return to work programs. In
general, cost-effectiveness analyses are determined largely by the productivity costs and, thus,
their appropriate assessment in economic evaluation is of paramount importance. However, the
comparability across cost of illness and costeffectiveness studies is hampered by substantial
differences in costs items considered, methods
used for measuring sickness absence and presenteeism, and actual valuation of, for example, a day
absent from work.
This chapter will present principles of economic evaluation of disability, sickness absence,
and productivity loss at work. First, some basic
concepts and deﬁnitions are discussed in Sect. 3.2.
Section 3.3 further explores the relevance of elements of productivity loss in speciﬁc counties
and disease categories. Section 3.4 describes and
comments on the important methodological
debates regarding the valuation of productivity
costs, whereas Sect. 3.5 addresses the perspective
of the analysis. We conclude with a brief discussion and research agenda in Sect. 3.6.
Some Basic Concepts
A central concept in this chapter is the term productivity costs. In health economics in general
and especially in the ﬁeld of economic evaluation
of health care and occupational medicine, we
deﬁne productivity costs as “the costs associated
with production loss and replacement due to illness, disability and death of productive persons,
both paid and unpaid” (Brouwer et al. 1999).
Although the deﬁnition above refers to paid and
unpaid work, in practice, most research focuses
on productivity costs related to paid work.
Productivity costs can be substantial when illness and treatment affect the productivity of
workers. Productivity costs are present in the following circumstances:
• In case of unscheduled absence from work
(due to health problems)
• In case of reduced productivity at work: one
might work with health problems that will
constrain and limit a worker to carry out his
regular activities and, this may lead to a lower
productivity (also called efﬁciency loss or
• In case of permanent disability to work
• In case of death (before the age of retirement)
Normal functioning at work, absenteeism, and
presenteeism can be interrelated. Brouwer et al.
(2005) showed (see Fig. 3.1) that presenteeism
often occurs before or after absenteeism, when
health problems do not completely inhibit workers being productive at work. Presenteeism is
also relevant for return to work programs, when
partially recovered workers return to their work
place, as illustrated by Lötters et al. (2005).
Productivity costs are sometimes also called
indirect nonmedical costs, as these costs represent a more indirect economic consequence of
disease, which become manifest outside the
health care sector. (For comparison, hospital
treatment costs for a disease are a part of the socalled direct medical costs.) However, for clarity
we prefer the term productivity costs.
In economic evaluation studies that analyze
the cost-effectiveness of occupational interventions, several perspectives can be taken, i.e., the
societal perspective, governmental perspective,
ﬁrm perspective, or workers’ perspective
(Drummond et al. 2005; Tompa et al. 2008) (see
Chap. 23). For economic evaluation studies of
health care programs Drummond et al. (2005)
strongly advise to use the societal perspective, as
the costs and beneﬁts of health (occupational)
care programs often affect several actors in society (differently) and are often ﬁnanced by public
All perspectives have to deal with prospects
and consequences. By now some workplacebased intervention studies undertake economic
analyses (Tompa et al. 2008). Most of these economic evaluations of workplace interventions
were conducted from the perspective of the ﬁrm/
company (Tompa et al. 2008). This is understandable, as the employer is an important stakeholder, who in the case of sick workers is
primarily confronted with productivity losses
and costs to maintain the production. However,
as productivity costs might depend on eligibility
criteria of social security beneﬁts and allocation
Work Absenteeism and Productivity Loss at Work
Fig. 3.1 An illustration of the possible relationship
between productivity and QOL. Q1 represents the level of
health above which a person is fully productive and below
which one experiences presenteeism (i.e., a person is pres-
ent at work but with reduced productivity); Q2 represents
the level of health below which a person will be absent
of these costs to different stakeholders, and are
also inﬂuenced by access and quality of occupational health and health care (that may fall on
other actors than the employer), it is in general
advisable to take the societal perspective.
However, the cost of productivity losses as an
argument/motivator to change policies and
implement occupational health interventions
makes the individual and company perspectives
also important because these stakeholders have
different interests or do not have the same
beneﬁts. The situation may even be more complex in North American and Australian jurisdictions, where responsibility for costs depends on
work-relatedness of the illness and work accidents and occupational disorders are being separately dealt with by Workers Compensation
Boards (WCB). In these jurisdictions, the
employer may be charged back for disability following experience rating, depending on the number and severity of previous work disability
cases. Also, a worker having a very reduced productivity level due to an occupational accident or
disorder may be less costly “at work” than absent
as his/her salary is not augmented by supplementary charges from the WCB: presenteeism with
zero productivity is less deleterious from the
perspective of the employer than absenteeism
and is much less costly from the perspective of
the WCB (see Chaps. 12 and 10).
The Relevance of Productivity
Losses and Costs
During the last decades abundant material has
been published, demonstrating the large amount
of productivity losses and associated costs related
to illness. We cannot discuss all evidence, but we
will summarize the main highlights, illustrated
by results of recent research.
In an extensive study by the OECD it appears that
worldwide the absence from work in general varies
between 1 and 7% of total working time (OECD
2010). The Nordic European countries show the
highest absence rates, e.g., Norway almost 7%,
Sweden 5%, and Finland 4–5% belong to the top
three (OECD 2010) (see Chap. 1).
M. Koopmanschap et al.
Absenteeism as a result of health problems is
clearly most prominent for musculoskeletal disease (mainly back pain) and mental disorders
(especially depression) (Goetzel et al. 2004). For
example, McDonald et al. (2011) reported that
among US workers with musculoskeletal pain
7% lost workdays due to absenteeism. In the
Netherlands, 46% workers with low back pain
being treated by a physiotherapist were absent at
least one day from work during the previous 6
weeks (Hoeijenbos et al. 2005). From patients
with subthreshold depression, Smit et al. (2006)
estimated the mean annual costs of absence from
work to be 3,279 euros. Another example of the
prominence of mental disease is bipolar disorders. Almost half (43%) of the patients experiencing this disease were absent from work (on
average 55 days per year), resulting in US$ 3,037
productivity costs per person (Hakkaart-van
Roijen et al. 2004). For other diseases that constitute a smaller proportion of sick leave in most
occupational groups, less detailed information is
available from some studies (Goetzel et al. 2004;
Schultz et al. 2009).
Reduced Productivity at Work
The magnitude of reduced productivity at work
(i.e., presenteeism) due to health problems is not
negligible. In an extensive review, Schultz et al.
(2009) reported two nationwide studies among
workers with chronic health problems, and for 11
out of 18 diseases presenteeism exceeded 50% of
to total costs. About 22% of respondents in these
studies reported some time lost to nearly onethird of adults whose health problems interfered
with their work tasks.
Brouwer et al. (1999) reported in 1999 among
workers in a trade company that 7.9% had reduced
productivity during a week. Nonetheless, this
resulted in less than 1% of working time lost.
Meerding et al. (2005) found that 12% of workers
in high physical load jobs had reduced productivity. Among those with productivity loss the average lost work time was 2 h per day. For patients
with low back pain being treated by a physiotherapist, 52% reported reduced productivity at work,
which resulted in 2 h production loss per day
(Hoeijenbos et al. 2005). For the USA, McDonald
et al. (2011) reported that 30% of workers with
musculoskeletal pain were less productive at
The average annual costs due to lower productivity at work for patients with subthreshold
depression were estimated to be 3,175 euros
(Smit et al. 2006).
In a study by Lötters et al. (2005) among Dutch
industrial and health care workers, loss in productivity was measured after returning to work fully
in the regular job after a substantial sick leave
period (median 84 days). Among those with selfreported productivity (using the QQ method)
(Brouwer et al. 1999; Koopmanschap 2005) the
median of productivity loss on an 8-h working
day due to MSD was 1.6 h shortly after RTW.
A worse physical health, more functional disability, and a poorer relation with the supervisor
were associated with the presence of productivity
loss shortly after RTW (Lötters et al. 2005). These
ﬁndings correspond to the presenteeism preceding and following absenteeism as illustrated in
the beginning of this chapter. Productivity losses
might occur due to the fact that the worker is not
fully recovered, despite the fact that he has
regained his normal working activity.
All these studies have shown that presenteeism contributes substantially to the estimated
total costs of disease among workers. The comparability across studies is poor, since methods of
lost productivity and associated costs vary substantially and are also inﬂuenced by local and
national arrangements with regard to compensation for illnesses and diseases.
Data on permanent disability differ substantially
across countries, as a result of variation in social
security arrangements. Social security arrangements (such as for unemployment or early retirement) may act to some extent as communicating
vessels depending on speciﬁc eligibility criteria.
As with sickness absence rates, the Nordic
European countries also show high disability
Work Absenteeism and Productivity Loss at Work
beneﬁt rates going from 7 to 10% of the working
force (WHO 2010). This is reﬂected in the high
proportion of GDP spent on disability and
sickness compensation. While the OECD countries spent on average approximately 1.9%,
Norway, Sweden, and the Netherlands are clear
outliers with 4.8, 3.6, and 3.7%, respectively.
Compared to countries such as Canada (0.5%)
and United States (1.7%) this is certainly high
(see Chap. 1).
Given the importance of absence from work
and reduced productivity at work as shown above,
it is very surprising that a recent meta-analysis of
economic evaluation studies of health care interventions targeted at patients with depressive disorders showed that only 25 out of 81 studies
included productivity costs (Krol et al. 2011). As
outlined in the introduction, the decision whether
to include presenteeism in productivity costs has
also compromised comparisons of cost of illness
studies across different diseases. However, given
the importance of productivity costs, we expect
that the number of economic evaluation studies
including both sick leave and productivity loss at
work will increase in the nearby future.
The Price Component
of Productivity Costs
After correct measuring and estimating, productivity loss due to health problems should preferably be valued in monetary terms, in order to
facilitate comparison of costs across disease categories and intervention programs.
The monetary valuation of productivity loss
has been the subject of considerable debate during the last decade (Koopmanschap et al. 1995;
Brouwer et al. 1997). Thus far no complete consensus exists among health economists with
respect to the best approach. The debate on valuation of sickness absence and disability focuses
on the duration of economic consequences to be
considered, as exempliﬁed in the human capital
and friction cost methods. With respect to the
valuation of sickness absence as well as productivity loss at work another debate centers on compensation mechanisms, whereby productivity is
not (completely) lost but shifted towards a later
period or towards other workers. Hence, we ﬁrst
present the two main methods used to value productivity losses and then discuss compensation
The Human Capital Method
The human capital method values total production lost due to illness, disability, or premature
death by calculating the total period of absence
(or disability or from death until the retirement
age) and subsequently multiplying this by the
wage rate (or an average expected wage rate for
the relevant period) of the absent worker.
The mainstream neoclassical economic theory
suggests that the productive value of a worker
equals his or her wage rate, at the margin. Since
in the cases of disability or death the patient is
absent for a long period of time, the cost calculations in these cases will be especially high.
Replacement of workers is not considered to
reduce productivity costs at the societal level in
this method, since full employment is assumed.
In particular, cost calculations for premature
death and disability yield very high results in
this method, and several authors have argued
that the estimations of productivity costs calculated with the human capital method would be a
maximum estimate, estimating possible productivity costs rather than actual productivity costs
(Koopmanschap and van Ineveld 1992).
The Friction Cost Method
The criticism of the human capital method is that
it ignores the possibility, at the societal level, that
an absent worker is replaced, and this induces the
development of the friction cost method
(Koopmanschap et al. 1995).
The essence of this method is that absent
workers will be replaced after an adaptation
period (the friction period), and in this way further production losses may subsequently be prevented. The friction period was assumed to be
equal to an average vacancy period, the period it
M. Koopmanschap et al.
takes to ﬁnd a suitable replacement of an absent
worker on the labor market, plus an additional
period (roughly estimated as 4 weeks) allowing
employers to start searching on the labor market
and training after hiring a new employee
(Koopmanschap et al. 1995). Recently, Erdogan,
Koopmanschap, and Bouwmans estimated the
friction period in ﬁve European countries in 2008
to be between 60 and 95 days (Erdogan submitted).
The value of the production losses is not estimated by using wage rates, but by estimating the
added value of a worker. After the friction period,
there are no additional productivity costs, except
for longer-term macroeconomic costs, as relatively high national levels of absence and disability from work might raise labor costs per unit of
production which lowers competitiveness on the
world market, limiting export and economic
growth (Koopmanschap et al. 1995). Zhang
et al. (2011) commented that the friction cost
method is not an alternative for the human capital
approach (as suggested by some authors), but a
reﬁnement, as it adjusts for worker replacement
in a friction period. Whether adjustment or
reﬁnement, it should be noted that the estimates
of productivity costs differ substantially between
these methods; see for example Koopmanschap
et al. (1995). (For details on friction and human
capital methods, see Chap. 4.)
The Debate on the Length
of Economic Consequences
The proponents of the human capital approach
and the friction cost method discussed the way to
value productivity costs in the health economic
literature. The main critical remark regarding the
friction cost method was that it would not value
the scarce time sacriﬁced by the person who
replaced the sick worker. However, the friction
cost method assumes that the leisure time
sacriﬁced by the formerly unemployed person
who takes up a new job to replace a worker fallen
ill will be valued in terms of quality of life. At
the level of society, the amount of leisure time
remains the same (the sick worker has more leisure time, the replacer less). The fact that the
sick worker might be less able to enjoy this
increase in leisure time fully is being captured in
terms of quality of life. For further details on this
discussion, see for example Weinstein et al.
(1997), Brouwer et al. (1997), and Zhang et al.
It is crucial to understand whether the two main
valuation methods as discussed above may lead
to different approaches to measure and value the
elements of productivity costs, especially shortterm absence from work and reduced productivity at work. Both approaches need information on
frequency and length of absence from work due
to disease and, when relevant, reduced productivity at work. However, the friction cost method
leaves open the possibility that work lost during
short-term absence might partially be compensated by the sick worker after return to work or
by colleagues. Hence some authors ask patients/
workers questions regarding these compensation mechanisms (Jacob-Tacken et al. 2005).
Incorporating these compensation mechanisms
further lowers estimates of productivity costs. On
the other hand, authors as Pauly et al. (2002) state
that absence of speciﬁc crucial workers (e.g., in
small teams) might have multiplier effects on
productivity of others. This would imply that productivity loss/costs due to absence of one worker
could be higher than the value of his/her individual production. When this is relevant in speciﬁc
cases, measurement instruments for productivity
loss should take this into account.
Another element of the working situation of
the sick worker that might affect the magnitude
productivity loss/costs is the relevance of deadlines. The more important the deadlines, the less
possibilities to postpone work or compensate
work loss at low cost (Pauly et al. 2002; Nicholson
et al. 2006). Meeting deadlines in case of illness
might necessitate labor reserves within organizations, which also has costs.
Also workplace-related factors have shown to
be related to productivity loss in general (absenteeism and presenteeism), such as lack of control
Work Absenteeism and Productivity Loss at Work
on the job, relation with the supervisor, thermal
climate, lightning condition, and regular disturbances (Alavinia et al. 2009; Lötters et al. 2005;
Niemela et al. 2002, 2006). Although workrelated factors surely are important to consider
when taken into account, productivity loss, the
severity of health problems, and work limitations
to these problems seem to have more effect on
productivity loss (Alavinia et al. 2009; Lötters
et al. 2005; Meerding et al. 2005).
Reviews about measuring presenteeism show
that several different measurement instruments
are commonly used (Mattke et al. 2007; Zhang
et al. 2011; Schultz et al. 2009), which generate
widely varying estimates of productivity loss
(Zhang et al. 2011). On the basis of the collective
opinion of stakeholder representatives (using the
Delphi method), recommendations for estimating the cost of productivity loss across all types
of health problems from a company’s perspective
have been formulated for presenteeism. The core
recommendation is to determine the volume of
work loss, and subsequently multiply this volume by an average or function-speciﬁc (daily or
hourly) salary. Furthermore it is suggested to add
the cost related to coworker overtime, if paid out,
and to subtract the amount of normal working
hours that direct coworkers take over work from
their less effective colleague as a buffer (Uegaki
et al. 2007).
This brings about another discussion around
presenteeism, namely whether or not it is feasible
to monetize the measure of productivity due to
presenteeism loss in a valid and precise way
(Schultz et al. 2009). As appeared from the abovementioned Delphi study by Uegaki et al. (2007),
several corrections can be applied on the costs
and consequences calculated from presenteeism;
furthermore, other studies additionally have indicated that other factors such as teamwork determine the magnitude of the consequences of
presenteeism (Pauly et al. 2008). So the effect of
productivity loss might have different implications
in different work settings; this hampers a valid
uniform measurement of productivity loss, especially the presenteeism part.
A related complicated question is how to handle long-term presenteeism. In case of chronic
diseases, workers might be working structurally
below normal standards. According to the human
capital approach, one might hypothesize that the
wage of such workers might be adjusted downwards, in order to match their lower productivity.
Applying the friction cost method, it probably
depends on the employer’s response. If the
employer observes the reduced productivity
(sooner or later), he might try to reduce the wage
(or ﬁre the worker) and/or look for another (parttime additional) worker, who can make up for the
work loss. The amount of productivity costs
involved will depend on many circumstances,
among which the ﬂexibility of the labor market
and the level of unemployment.
There is evidence of a clear downward trend
in career development for people with a health
problem. Considering certain chronic (or longlasting) diseases such as depression, rheumatoid
arthritis, and diabetes, it shows that there is clear
work disability due to these diseases (Adler et al.
2006; Baanders et al. 2002; Tunceli et al. 2005;
Lavigne et al. 2003; Ng et al. 2001). For instance,
for diabetes this work disability is due to fatigue
and concentration problems, having to perform
shift-work and suffering diabetes complications
(Baanders et al. 2002; Tunceli et al. 2005; Lavigne
et al. 2003; Ng et al. 2001).
Eventually, these health problems might even
lead to a structural lower number of working
hours as compared to workers without a chronic
health problem; this indeed was shown in a comprehensive research among OECD countries conducted by the OECD (WHO 2010). From this
study it appeared that when employed, persons
with disability work part time more often than
other persons in paid employment (10% points)
Another problem around measuring presenteeism is the correlation real-time measured productivity loss. Only a few studies measured actual
production output and related that to self-reported
M. Koopmanschap et al.
measures of presenteeism. In a study among ﬂoor
layers by Meerding et al. (2005), using the QQ
scale (Brouwer et al. 1999), it was shown that
actual production output was signiﬁcantly correlated with the mean self-reported productivity of
the team (r = 0.48). However, in the same study it
was not feasible to measure the individual production of members of road pavers teams (3–6
persons), which illustrates the complexity of
measuring individual production in many work
settings. In a study by Lerner et al. (2003) among
call center employees using the Work Limitation
Questionnaire (Lerner et al. 2001) as a measure
of productivity loss, it was found that every 10%
increase in the job limitations reported with the
WLQ, the actual production output declined
Expenditure on Social Security
as Proxy for Costs?
It might seem sensible to use the amount of social
security beneﬁts paid related to absence and disability as a proxy of societal productivity costs.
However, this is not advisable, as the premiums
and beneﬁts are just transfer payments, a redistribution of wealth within society from premium
payers to beneﬁt receivers. For society at large,
this does not represent an economic loss or gain.
What society really loses when workers get ill
and work disabled is the value of production loss,
which decreases wealth and increases the scarcity of societal resources (Drummond et al.
2005). Besides this redistribution of wealth
within a country it needs to be emphasized that
social security systems across countries differ.
Costs, beneﬁts, and incentives to return to work
(for both employer and employee) can be very
different and subsequently will inﬂuence the
time-window in which this takes place. For
example, in the Netherlands the employer pays 2
years of sick pay before the social security beneﬁt
comes in. So, the incentive for an early return to
work largely falls on the employer. The costs
made in this regard are often not allocated as
being societal costs.
In economic evaluation studies of health care
programs, taking the societal perspective is
advocated (Drummond et al. 2005). As a consequence, productivity costs, when relevant, should
be included in studies that address the costeffectiveness of health and occupational interventions. Within health care this is quite
straightforward, as the users of these economic
evaluation studies are policymakers, who have
to decide whether to include an intervention in
the basic beneﬁt package that is ﬁnanced by
taxes and/or social security contributions (i.e.,
public resources) (see Chaps. 12, 4, and 23).
But, when the Minister of Health has to choose
between a saving of ten million euros on the
health care budget or a saving of ten million euros
in productivity loss (for society’s wealth at large
it should make no difference), the minister might
prefer the budget saving. This balance might only
be shifted when other parts of the government (or
employer organizations) underline the importance of the productivity gain. When looking at
occupational interventions, the beneﬁts of an
intervention might be twofold: better health for
the workers and productivity gains for the
employer. When the productivity gains are substantial and the intervention is not too expensive,
the cost–beneﬁt ratio might be positive for the
organization, which can view it as a sensible private investment. In case of net costs and health
gains, the intervention might be cost-effective for
society (it costs, e.g., only 3,000 euros per QALY
gained), but not proﬁtable for the organization to
start up as only investor. An example of a skewed
distribution of cost and beneﬁts is a recent evaluation of interventions for occupational asthma
and rhinitis among bakery workers (Meijster et al.
2011). This study showed that for an intervention
employers were responsible for 63% of the
required investments, but reaped only 48% of the
beneﬁts. In this speciﬁc situation coﬁnancing of
the intervention (or other types of ﬁnancial incentives) by government and/or health insurers might
Work Absenteeism and Productivity Loss at Work
facilitate implementation of such a program.
It must be stated that in other situations and jurisdictions, the distribution of costs and beneﬁts
over stakeholders may be different and, thus, one
would arrive at a different conclusion.
Discussion and Research
In this paragraph we will brieﬂy discuss the key
ﬁndings and especially the unanswered questions
related to the costs of work absenteeism and productivity loss at work.
Reviewing the literature, it is clear that the
costs of disease-related absence from work and
productivity loss at work can be substantial, especially for musculoskeletal and mental disorders.
However, more information is needed on the work
situations where health problems result in productivity loss and those work situations where this
will not be the case (van der Berg et al. 2011). The
debate regarding the valuation of absenteeism
reveals that especially the extent of compensation
mechanisms and the impact of team production,
deadlines, etc. on the value of productivity loss
should be considered in future analyses.
In addition, we observed many ways to measure
and value productivity loss at work (presenteeism).
Initiatives to improve the measurement and valuation of presenteeism are currently being undertaken
worldwide. Especially, the measurement and valuation of long-term presenteeism (e.g., due to
chronic and/or episodic disorders) should become
subject of future research, as it might have a substantial impact on the employability and working
careers of these chronically ill persons.
As observed, the number of cost-effectiveness
studies of occupational health interventions is
growing, but is still too small to guide policy
makers in choosing between interventions. These
cost-effectiveness studies should include productivity costs (as these are the main cost driver),
which is still not often the case.
Economic evaluation will increasingly play a
role in decisions about provision of occupational
health programs for ill workers or workers on
sick leave. Information on cost-effectiveness of
different intervention programs may guide the
occupational health professional towards
improved decisions regarding priorities in work
rehabilitation. Some caution is required, since the
cost–beneﬁts of an RTW intervention among
workers on sick leave is not only determined by
the estimated effectiveness of the intervention
and associated costs and beneﬁts of the intervention, but also heavily depend on the natural course
of RTW in the target population, the timing of the
enrollment of persons into the intervention, and
the duration of the intervention. These latter three
factors are seldom taken into consideration in
decisions about implementing an RTW program
(van Duin et al. 2010).
The progress in evidence-based occupational
health care will require further development and
reﬁnement of tools and methods used for economic evaluation. Insight into the economical
consequences of adverse effects of illness in
addition to consideration of the many workrelated risk factors on workers’ health and disability can provide unique opportunities to
demonstrate to decision makers in companies
and government the necessity of implementing
workplace interventions and adequate provisions
of occupational health services that can reduce
the burden of work disability.
A complication for policies that potentially
reduce productivity costs is the fact that costs and
beneﬁts (both ﬁnancial and health) often do not
fall upon the same actor, limiting the will to
implement these. There is no simple solution for
this, but showing the total societal gains and
designing (ﬁnancial) incentives for various actors
might help to motivate parties to work towards
common goals. Much more active input from all
parties could facilitate innovative evidence-based
interventions that could pay off!
Adler, D. A., McLaughlin, T. J., Rogers, W. H., Chang, H.,
Lapitsky, L., & Lerner, D. (2006). Job performance
deﬁcits due to depression. The American Journal of
Psychiatry, 163(9), 1569–1576.
Alavinia, S. M., de Boer, A. G., van Duivenbooden, J. C.,
Frings-Dresen, M. H., & Burdorf, A. (2009).
Determinants of work ability and its predictive value
for disability. Occupational Medicine (London), 59(1),
Baanders, A. N., Rijken, P. M., & Peters, L. (2002).
Labour participation of the chronically ill. A proﬁle
sketch. European Journal of Public Health, 12,
Brouwer, W. B. F., Koopmanschap, M. A., & Rutten, F. F.
H. (1997). Productivity costs measurement through
quality of life? A response to the recommendation
of the Washington Panel. Health Economics, 6,
Brouwer, W. B., Koopmanschap, M. A., & Rutten, F. F.
(1999). Productivity losses without absence:
Measurement validation and empirical evidence.
Health Policy, 48(1), 13–27.
Brouwer, W. B., Meerding, W. J., Lamers, L. M., &
Severens, J. L. (2005). The relationship between productivity and health-related QOL: An exploration.
PharmacoEconomics, 23(3), 209–218.
Drummond, M. F., Sculpher, M. J., Torrance, G. W.,
O’Brien, B., & Stoddart, G. L. (2005). Methods for the
economic evaluation of health care programmes (3rd
ed.). Oxford: Oxford University Press.
Erdogan, Bouwmans, Koopmanschap Estimation of
Productivity Costs using FrictionCost Approach: New
Evidence using National Data (submitted)
Goetzel, R. Z., Long, S. R., Ozminkowski, R. J., et al.
(2004). Health, absence, disability, and presenteeism
cost estimates of certain physical and mental health
conditions affecting U.S. employers. Journal of
Occupational and Environmental Medicine, 46,
Hakkaart-van Roijen, L., Hoeijenbos, M. B., Regeer, E. J.,
Ten Have, M., Nolen, W. A., Veraart, W. M., et al.
(2004). The societal costs and quality of life of patients
suffering from bipolar disorder in the Netherlands.
Acta Psychiatrica Scandinavica, 110(5), 383–392.
Hoeijenbos, M. B., Bekkering, G. E., Lamers, L. M.,
Hendriks, H. J. M., van Tulder, M. W., &
Koopmanschap, M. A. (2005). Cost-effectiveness of
an active implementation strategy for the Dutch physiotherapy guideline for low back pain. Health Policy,
Jacob-Tacken, K. H. M., Koopmanschap, M. A., Meerding,
W. J., & Severens, J. L. (2005). Correcting for compensating mechanisms related to productivity costs in
economic evaluations of health care programs. Health
Economics, 14, 435–443.
Koopmanschap, M. A. (2005). PRODISQ: A modular
questionnaire on productivity and disease for economic evaluation studies. Expert Review of
Pharmacoeconomics & Outcomes Research, 5(1),
Koopmanschap, M. A., Rutten, F. F. H., van Ineveld, B.
M., & van Roijen, L. (1995). The friction cost method
for estimating the indirect costs of disease. Journal of
Health Economics, 14, 171–189.
M. Koopmanschap et al.
Koopmanschap, M. A., & van Ineveld, B. M. (1992).
Towards a new approach for estimating indirect costs
of disease. Social Science & Medicine, 34(9),
Krol, M., Papenburg, J., Koopmanschap, M., & Brouwer,
W. (2011). Do productivity costs matter? The impact
of including productivity costs on the incremental
costs of interventions targeted at depressive disorders.
PharmacoEconomics, 29(7), 601–619.
Lambeek, L. C., van Tulder, M. W., Swinkels, I. C.,
Koppes, L. L., Anema, J. R., & van B, W. (2011). The
trend in total cost of back pain in The Netherlands in
the period 2002 to 2007. Spine, 36(13), 1050–1058.
Lavigne, J. E., Phelps, C. E., Mushlin, A., & Lednar, W.
M. (2003). Reductions in individual work productivity
associated with type 2 diabetes mellitus.
PharmacoEconomics, 21, 1123–1134.
Lerner, D., Amick, B. C., 3rd, Lee, J. C., Rooney, T.,
Rogers, W. H., Chang, H., et al. (2003). Relationship
of employee-reported work limitations to work productivity. Medical Care, 41(5), 649–659.
Lerner, D., Amick, B. C., 3rd, Rogers, W. H., Malspeis, S.,
Bungay, K., & Cynn, D. (2001). The work limitations
questionnaire. Medical Care, 39(1), 72–85.
Lötters, F., Meerding, W. J., & Burdorf, A. (2005).
Reduced productivity after sickness absence due to
musculoskeletal disorders and its relation to health
outcomes. Scandinavian Journal of Work, Environment
& Health, 31(5), 367–374.
Mattke, S., Balakrishnan, A., Bergamo, G., & Newberry,
S. J. (2007). A review of methods to measure healthrelated productivity loss. The American Journal of
Managed Care, 13(4), 211–217.
McDonald, M., daCosta DiBonaventura, M., & Ullman,
S. (2011). Musculoskeletal pain in the workforce. The
effects of back, arthritis, and ﬁbromyalgia pain on
quality of life and work productivity. Journal of
Occupational and Environmental Medicine, 53(7),
Meerding, W. J., IJzelenberg, W., Koopmanschap, M. A.,
IJzelenberg, W., & Severens, J. L. (2005). Health
problems lead to considerable productivity loss at
work among workers with high physical load jobs.
Journal of Clinical Epidemiology, 58(5), 517–523.
Meijster, T., van Duuren-Stuurman, B., Heederik, D.,
Houba, R., Koningsveld, E., Warren, N., et al. (2011).
Cost-beneﬁt analysis in occupational health: A comparison of intervention scenarios for occupational
asthma and rhinitis among bakery workers.
Occupational and Environmental Medicine, 68,
Ng, Y. C., Jacobs, P., & Johnson, J. A. (2001). Productivity
losses associated with diabetes in the U.S. Diabetes
Care, 24, 257–261.
Nicholson, S., Pauly, M. V., Polsky, D., Sharda, C., Szrek,
H., & Berger, M. L. (2006). Measuring the effects of
work loss on productivity with team production.
Health Economics, 15, 111–123.
Work Absenteeism and Productivity Loss at Work
Niemela, R., Rautio, S., Hannula, M., & Reijula, K.
(2002). Work environment effects on labor productivity: An intervention study in a storage building.
American Journal of Industrial Medicine, 42(4),
Niemela, R., Seppanen, O., Korhonen, P., & Reijula, K.
(2006). Prevalence of building-related symptoms as an
indicator of health and productivity. American Journal
of Industrial Medicine, 49(10), 819–825.
Pauly, M. V., Nicholson, S., Polsky, D., Berger, M. L., &
Sharda, C. (2008). Valuing reductions in on the job
illness: Presenteeism from managerial and economic
perspectives. Health Economics, 17(4), 469–485.
Pauly, M. V., Nicholson, S., Xu, J., Polsky, D., Danzon,
P. M., Murray, J. F., et al. (2002). A general model of
the impact of absenteeism on employers and employees. Health Economics, 11, 221–231.
Schultz, A. B., Chen, C. Y., & Edington, D. W. (2009).
The cost and impact of health conditions on presenteeism to employers: A review of the literature.
PharmacoEconomics, 27(5), 365–378.
Smit, F., Willemse, G., Koopmanschap, M., Onrust, S.,
Cuijpers, P., & Beekman, A. (2006). Cost-effectiveness
of preventing depression in primary care patients:
Randomised trial. The British Journal of Psychiatry,
Stock, S., Redaelli, M., Luengen, M., et al. (2005).
Asthma: Prevalence and cost of illness. European
Respiratory Journal, 25, 47–53.
Tompa, E., Culyer, A. J., & Dolinschi, R. (2008). Economic
evaluation of interventions for occupational health
and safety. Developing good practice. Oxford: Oxford
Tunceli, K., Bradley, C. J., Nerenz, D., Williams, I. K.,
Pladevall, M., & Lafata, J. E. (2005). The impact of
diabetes on employment and work productivity.
Diabetes Care, 28, 2662–2667.
Uegaki, K., de Bruijne, M. C., Anema, J. R., van der Beek,
A. J., van Tulder, M. W., & van Mechelen, W. (2007).
Consensus-based ﬁndings and recommendations for
estimating the costs of health-related productivity loss
from a company’s perspective. Scandinavian Journal
of Work, Environment & Health, 33(2), 122–130.
van der Berg, T. I. J., Robroek, S. J. W., Plat, J. F.,
Koopmanschap, M. A., & Burdorf, A. (2011). The
importance of job control for workers with decreased
work ability to remain productive at work. International
Archives of Occupational and Environmental Health,
van Duin, M., Eijekemans, M. J., Koes, B. W.,
Koopmanschap, M. A., Burton, A. K., & Burdorf, A.
(2010). The effects of timing on the cost-effectiveness
of interventions for workers on sick leave due to low
back pain. Occupational and Environmental Medicine,
van Tulder, M. W., Koes, B. W., & Bouter, L. M. (1995).
A cost-of-illness study of back pain in The Netherlands.
Pain, 62, 233–240.
Weinstein, M. C., Siegel, J. E., Garber, A. M., Lipscomb,
J., Luce, B. R., Manning, W. G., et al. (1997).
Productivity costs, time costs and health-related quality of life: A response to the Erasmus Group. Health
Economics, 6, 505–510.
WHO. (2010). Sickness, disability and work. Breaking the
barriers. A synthesis of ﬁndings across OECD countries. Paris: OECD Publishing.
Zhang, W., Bansback, N., & Anis, A. H. (2011). Measuring
and valuing productivity loss due to poor health: A
critical review. Social Science & Medicine, 72,