Published on March 5, 2014
3 Work Absenteeism and Productivity Loss at Work Marc Koopmanschap, Alex Burdorf, and Freek Lötters This chapter will present principles of economic evaluation of disability, sickness absence, and productivity loss at work (also called presenteeism). Relevance and policy questions regarding health-related production loss are discussed. 3.1 Introduction The economic consequences of illness and disease have emerged as a key area of research, whereby cost of illness studies have invariably reported that the disease of interest will result in considerable costs due to disability, sickness absence, and productivity loss at work. One of the ﬁrst studies on societal costs due to back pain estimated the total costs to be approximately 4.2 billion euros (1.7% of the Gross National Product) in the Netherlands, whereby back pain was the ﬁfth most expensive disease for medically related costs and most expensive for indirect costs due to sickness absence and work disablement (van Tulder et al. 1995). The indirect costs (hereafter called productivity costs) contributed 93% to total costs, illustrating the importance of the consequences of disease for M. Koopmanschap (*) • F. Lötters Department of Health policy and Management, Erasmus University Rotterdam, P.O. Box 1738, 3000 DR Rotterdam, The Netherlands e-mail: firstname.lastname@example.org; email@example.com A. Burdorf Department of Public Health, Erasmus Medical Center, P.O. Box 2040, 3000 CA Rotterdam, The Netherlands e-mail: firstname.lastname@example.org work performance. An update showed that the total costs decreased from 4.3 billion euros in 2002 to 3.5 billion euros in 2007, which corresponded to a decrease in the share of the Gross National Product from 0.9 to 0.6% (Lambeek et al. 2011). Various studies on different diseases have shown similar results. A cost of illness study on asthma in Germany reported high costs for the German social insurance system, with productivity costs amounting to 75% of total costs and payment of sick beneﬁts through the sickness funds amounting to 58% of these indirect costs (Stock et al. 2005). In a large study on almost 400,000 workers in the USA the direct and productivity cost were estimated for ten common health conditions. The productivity costs substantially exceeded the direct costs for all but one disease (heart disease). Within the productivity costs categories productivity loss at work while being limited due to a disease were far more important than sickness absence and short-term disability. In fact, these so-called presenteeism costs represented 18–60% of all costs for the ten conditions (Goetzel et al. 2004). A recent review of three studies indicated that for 18 different diseases presenteeism contributed between 14 and 73% (average 48%) to the total direct and indirect costs (Schultz et al. 2009). This chapter also demonstrated that studies on costs of illness may present widely varying results due to the methods used and the deﬁnition of indirect costs. Whereas the earlier studies have limited indirect costs to sickness absence-related costs, more recent studies have also incorporated presenteeism in indirect costs. P. Loisel and J.R. Anema (eds.), Handbook of Work Disability: Prevention and Management, DOI 10.1007/978-1-4614-6214-9_3, © Springer Science+Business Media New York 2013 31
M. Koopmanschap et al. 32 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. 3.2 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 presenteeism) • 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 resources. 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
3 Work Absenteeism and Productivity Loss at Work 33 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 from work 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). 3.3 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. 3.3.1 Absenteeism 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. 34 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). 3.3.2 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 work. 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. 3.3.3 Permanent Disability 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
3 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. 3.4 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 35 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 mechanisms. 3.4.1 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). 3.4.2 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. 36 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.) 3.4.3 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. (2011). 3.4.4 Compensation Mechanisms 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
3 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). 3.4.5 Presenteeism 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 37 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) (WHO 2010). 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. 38 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 approximately 4–5%. 3.4.6 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. 3.5 Productivity Costs, Whose Concern? 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
3 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. 3.6 Discussion and Research Agenda 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 39 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! References 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).
40 Determinants of work ability and its predictive value for disability. Occupational Medicine (London), 59(1), 32–37. Baanders, A. N., Rijken, P. M., & Peters, L. (2002). Labour participation of the chronically ill. A proﬁle sketch. European Journal of Public Health, 12, 124–130. 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, 253–259. 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, 398–412. 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, 75, 85–98. 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), 23–28. 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), 1005–1010. 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), 765–770. 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, 739–745. 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.
3 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), 328–335. 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, 188, 330–336. 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 University Press. Tunceli, K., Bradley, C. J., Nerenz, D., Williams, I. K., Pladevall, M., & Lafata, J. E. (2005). The impact of 41 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, 84, 705–712. 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, 67, 744–750. 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, 185–192.
The economic consequences of illness and disease have emerged as a key area of research, whereby cost of illness studies have invariably reported that the ...
Opinions expressed by Forbes ... Causes of Absenteeism. People miss work for a ... forms of absenteeism and can affect productivity and ...
... 21 February 2013. Work Absenteeism and Productivity Loss at Work. ... Regarding the monetary valuation of absenteeism, ...
BUILDING JOB SATISFACTION AMONG EMPLOYEES IN AUTOMOTIVE ... no work. Absenteeism reduces ... effort to reduce work stress, improve productivity, ...
Is absenteeism related to ... influencing an employee’s motivation to attend work. Absenteeism is a term used to ... Productivity is reduced to ...
... © Springer Science+Business Media New York 2013 ... Work Absenteeism and Productivity Loss at Work ... Normal functioning at work, absenteeism, ...
1. 3Work Absenteeism and Productivity Loss at Work Marc Koopmanschap, Alex Burdorf, and Freek LöttersThis chapter will present principles of economic ...
In 2013 in the UK the CIPD ... absenteeism and reduced productivity among other workers who try to work while ill. Work forces often excuse absenteeism ...
This study concludes that employers can reduce absenteeism, lost productivity and ... particularly where certain work ... workplace absenteeism.
Productivity » Labor Productivity ... Illness-related work absences in January 2013 highest since February 2008. ... U.S. Bureau of Labor Statistics ...