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  • 1.
    Henriksson, Martin
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Siverskog, Jonathan
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences.
    Johannesen, Kasper
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences.
    Eriksson, Thérèse
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences.
    Tröskelvärden och kostnadseffektivitet: innebörd och implikationer för ekonomiska utvärderingar och beslutsfattande i hälso- och sjukvården2018Report (Other academic)
    Abstract [en]

    The results of health economic evaluations are often reported as an incremental cost-effectiveness ratio (ICER) indicating the additional cost in relation to the additional benefit of providing the health care technology under evaluation compared with a relevant alternative. The health care technology may be a prevention program, a diagnostic method, a surgical procedure or a pharmaceutical treatment (henceforth we refer to interventions as a general term for all health care technologies). Commonly, benefits are measured in health-related outcomes such as the quality-adjusted life year (QALY). To interpret and operationalize ICERs in health care decision making, they have to be compared with some benchmark value. This value of a QALY when an intervention can be interpreted as being cost-effective is often referred to as the cost-effectiveness threshold in the literature. Ambitious attempts to estimate this threshold value have recently been reported, contributing with new knowledge in the field. In light of this research it is also evident that there are different interpretations of the threshold and different views regarding what the threshold should represent. Different interpretations may lead to different policy conclusions as well as diverging interpretations of cost-effectiveness. The aim of this report is to describe different interpretations of the cost-effectiveness threshold, summarize the empirical evidence, and discuss the threshold and further research in a Swedish context. In the report, the two main definitions of cost-effectiveness thresholds appearing in the literature are covered. One definition of the threshold is the consumption value of health, or the willingness to pay for health, and may represent what individuals on the margin are willing to forego in consumption in order to obtain an additional QALY. This definition is sometimes referred to as a demand side threshold, and has been dubbed v in the literature. Another definition of the threshold is based on the productivity of the health care sector and is some-times referred to as the supply side threshold, dubbed k in the literature. With this approach, estimates of the marginal productivity of the health care sector can indicate if a new intervention generates more health than is expected to be forgone when displacing other health care (to fund the new intervention). In principle, the cost-effectiveness threshold with this definition should be the cost per QALY gained of the least cost-effective intervention still funded within the health care system. The implications of a wider societal perspective (including non-health care sectors) for the two definitions of the cost-effectiveness threshold are discussed in the report. It is argued that the marginal productivity of the health care sector always has to be considered if some opportunity costs of a new intervention fall on the health care sector. When opportunity costs of a new intervention in the health care sector fall on private consumption, the consumption value of health may also have to be considered. The answer to the question of which definition of the cost-effectiveness threshold is more appropriate or relevant is therefore that it depends on the perspective deemed relevant as well as where the opportunity costs are expected to fall. Empirical studies have to a larger extent focussed on estimating the consumption value of health (v) compared with the marginal productivity of the health care sector (k). Regarding estimates of both v and k, the empirical evidence regarding a Swedish context is limited. An English study is, as far as we are aware, the first attempt to explicitly estimate k based on large scale data. In this study, the cost-effectiveness threshold was estimated at a cost per QALY of £13,000. In an attempt to translate this estimate to a Swedish setting, a cost per QALY in the interval $21,000 to $27,000 has been presented. Studies attempting to estimate v report estimates of 30,000 to several million Swedish kronor.

    Much of the variation in results appears to be explained by methodological differences in the studies including: study design (online, interviews or surveys), response alternatives, statistical methods for analysing data, type of health evaluated (length of life, quality of life or both), certainty in evaluated health change, and whether the evaluated health change will be obtained by the respondent or someone else. Estimates of v in a Swedish setting are scarce when a general health change has been valued by a sample of the general public. The only identified study in the peer-reviewed literature with respondents from Sweden reports estimates in the interval 150,000 to 350,000 Swedish kronor. In a recent report available from the Swedish Institute for Health Economics (IHE) an estimated cost per QALY of 2.4 million is reported. It is concluded in the report that it is not possible to determine which definition of the cost-effective-ness threshold is most relevant or appropriate for health care decision making unless the purpose of the health care sector, and the relevant perspective are defined first. It is further concluded that regardless of the definition of the threshold, the empirical knowledge of marginal productivity of the health care sector (k) as well as the consumption value of health (v) is limited in a Swedish context. Further empirical studies are needed on both. Statistical modelling of available statistical resources may be a feasible approach for estimating the marginal productivity, while well conducted experiments, or methods to study revealed preferences by observing behaviour of individuals in real-life decision making may be feasible approaches for estimating the consumption value of health.

  • 2.
    Siverskog, Jonathan
    et al.
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences.
    Henriksson, Martin
    Linköping University, Department of Medical and Health Sciences, Division of Health Care Analysis. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Estimating the marginal cost of a life year in Sweden's public healthcare sector2019In: European Journal of Health Economics, ISSN 1618-7598, E-ISSN 1618-7601, Vol. 20, no 5, p. 751-762Article in journal (Refereed)
    Abstract [en]

    Although cost-effectiveness analysis has a long tradition of supporting healthcare decision-making in Sweden, there are no clear criteria for when an intervention is considered too expensive. In particular, the opportunity cost of healthcare resource use in terms of health forgone has not been investigated empirically. In this work, we therefore seek to estimate the marginal cost of a life year in Sweden's public healthcare sector using time series and panel data at the national and regional levels, respectively. We find that estimation using time series is unfeasible due to reversed causality. However, through panel instrumental variable estimation we are able to derive a marginal cost per life year of about SEK 370,000 (EUR 39,000). Although this estimate is in line with emerging evidence from other healthcare systems, it is associated with uncertainty, primarily due to the inherent difficulties of causal inference using aggregate observational data. The implications of these difficulties and related methodological issues are discussed.

  • 3.
    Sjö, Bo
    et al.
    Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences.
    Bekiros, Stelios
    IPAG Business School, Paris, France.
    Siverskog, Jonathan
    Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Medicine and Health Sciences.
    Uddin, Gazi Salah
    Linköping University, Department of Management and Engineering, Economics. Linköping University, Faculty of Arts and Sciences.
    Analyzing Contagion and Tail Dependence in Global Real Estate Markets using NonParametric Flexible Copulas2017Conference paper (Other academic)
    Abstract [en]

    The global financial crisis and the collapse of the collateralized debt obligation (CDO) market have brought increased attention to the proper modeling of housing price co-movements worldwide. We aim at detecting possible contagion effects in international real estate markets while accommodating dependence during extreme tail events. We propose a novel copula based approach incorporating second-moment effects that not only accounts for asymmetric tail dependence, but also allows for time-varying correlation in price movements. Unlike previous studies wherein static copula-based models are utilized, we extend our methodology by employing nonparametric copulas with the adjustment of flexible specification. Common Gaussian or mixture copulas lack the required tail features to capture the empirical stylized facts in housing markets. We proved the lack of monotonicity imposed by parametric methods was evidently not supported by our data. Using monthly data in seven major global markets, we confirm that prices do exhibit correlations that change over time, whilst more importantly their tail dependence structure for extreme losses strengthens in the midst of market turmoil.

    We indicated that especially during downturns, CDOs do not provide the level of diversification widely assumed before the subprime crisis. Information on tail dependence would better allow policy makers to anticipate real estate prices on a global scale.

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