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      Friction Cost Estimates of Productivity Costs in Cost-of-Illness Studies in Comparison with Human Capital Estimates: A Review

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      Applied Health Economics and Health Policy
      Springer Science and Business Media LLC

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          Abstract

          <p class="first" id="P2">Cost-of-illness (COI) studies often include the “indirect” cost of lost production resulting from disease, disability, and premature death, which is an important component of the economic burden of chronic conditions assessed from the societal perspective. In most COI studies, productivity costs are estimated primarily as the economic value of production forgone associated with loss of paid employment (foregone gross earnings); some studies include the imputed value of lost unpaid work as well. This approach is commonly but imprecisely referred to as the human capital approach (HCA). However, there is a lack of consensus among health economists as to how to quantify loss of economic productivity. Some experts argue that the HCA overstates productivity losses and propose use of the friction cost approach (FCA) that estimates societal productivity loss as the short-term costs incurred by employers in replacing a lost worker. This review sought to identify COI studies published during 1995–2017 that used the FCA, with or without comparison to the HCA, and to compare FCA and HCA estimates from those studies that used both approaches. We identified 80 full COI studies (of which 75% focused on chronic conditions), roughly 5–8% of all COI studies. The majority of those studies came from three countries, Canada, Germany, and the Netherlands, that have officially endorsed use of the FCA. The FCA results in smaller productivity loss estimates than the HCA, although the differential varied widely across studies. Lack of standardization of HCA and FCA methods makes productivity cost estimates difficult to compare across studies. </p>

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          Most cited references99

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          Recommendations for Conduct, Methodological Practices, and Reporting of Cost-effectiveness Analyses: Second Panel on Cost-Effectiveness in Health and Medicine.

          Since publication of the report by the Panel on Cost-Effectiveness in Health and Medicine in 1996, researchers have advanced the methods of cost-effectiveness analysis, and policy makers have experimented with its application. The need to deliver health care efficiently and the importance of using analytic techniques to understand the clinical and economic consequences of strategies to improve health have increased in recent years.
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            The friction cost method for measuring indirect costs of disease.

            A new approach for estimating the indirect costs of disease, which explicitly considers economic circumstances that limit production losses due to disease, is presented (the friction cost method). For the Netherlands the short-term friction costs in 1990 amount to 1.5-2.5% of net national income (NNI), depending on the extent to which short-term absence from work induces production loss and costs. The medium-term macro-economic consequences of absence from work and disability reduce NNI by an additional 0.8%. These estimates are considerably lower than estimates based on the traditional human capital approach, but they better reflect the economic impact of illness.
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              Investment in Human Capital: A Theoretical Analysis

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                Author and article information

                Contributors
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Applied Health Economics and Health Policy
                Appl Health Econ Health Policy
                Springer Science and Business Media LLC
                1175-5652
                1179-1896
                December 2018
                August 9 2018
                December 2018
                : 16
                : 6
                : 765-778
                Article
                10.1007/s40258-018-0416-4
                6467569
                30094591
                8b49eff4-b1bb-4549-b1f6-585e12630cf1
                © 2018

                http://www.springer.com/tdm

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