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Economic methods and Social Costs Value Analysis (SCVA)

Conventional approaches to the economic evaluation of health services are typically based on the logic of cost effectiveness, i.e., the computation of incremental costs per QALY (quality-adjusted life year) gained. The logic, however, rests on a restrictive definition of value, as well as a large number of assumptions.  In turn, problematic conclusions may result, which in some cases may even be considered unethical. One limitation may be reliance on individual self-centered preferences for health states, not taking into account social non-selfish preferences.

Members of the DKFZ Division of Health Economics share an interest in the exploration of the conceptual and empirical underpinnings of the conventional model, with a vision to identify and test extensions or alternatives, which might be expected to better capture prevailing social norms and preferences. In addition to rigorous normative analysis and deliberation among stakeholders, any such approach will need robust information on health and health care related social preferences of citizens as a point of reference.

1. Social Costs Value Analysis (SCVA)

European social preferences measurement (ESPM) project



A comprehensive review of the literature on social preferences with regard to the allocation of health care resources indicated empirical support for a number of characteristics or "attributes" (beyond clinical effectiveness) of interventions. In particular, these include: 1) giving priority to the worst-off patients (in terms of severity, related to the ex ante health state); 2) prioritizing urgent interventions (urgency, because of the risk of major irreversible consequences without intervention, which may be conceptualized as an effectiveness); 3) not discriminating against persons in "double-jeopardy" (or, more generally, persons with comorbid conditions); 4) prioritizing health care for younger over older patients (age or the "fair innings" argument); and wishing to share resources with patients even if their treatment costs are high, in order not to disenfranchise them from a fair chance of access to effective care; and, albeit generally to a lesser extent, a number of further attributes. Critical questions remained due to the small size of many studies, heterogeneity of experimental settings, the potential for bias due to framing effects, and the level of information among respondents regarding the implications of their choices. Further issues were identified in relation to the stability of observed preferences and the validity of the resource constraint imposed in some of the studies.

Against this background, a research program has been initiated to investigate how citizens valuate selected characteristics (or "attributes", see below) of health care interventions, and how they weigh them against each other; to compare the valuation results obtained in the project with those based on the conventional logic of cost effectiveness; to assess the sensitivity of weights to the level of reflection and information offered to respondents and thus to potential framing effects; to generate learnings and provide a basis for subsequent studies, ultimately paving the way towards an exploration of international similarities and differences with regard to the valuation of the attributes tested, including an external validation of results by testing the agreement of respondents between their choices in the experimental setting, their policy implications, and their social preferences.

The first phase of the project focused specifically on the impact of rarity on the evaluation of health technologies. The assessment of interventions for rare and ultra-rare diseases can help anticipate many of the challenges arising in the context of precision medicine and its evaluation. Rare diseases thus represent an experimentation platform for the health care systems of tomorrow. This includes key evaluation principles, as the ones currently applied may turn out to be not yet "fit for purpose" because of too narrowly defined criteria for the proof of effectiveness and for the determination of social value.

The approach of the first study was a willingness to pay (WTP) design using discrete choice experiment (DCE) methodology. WTP was estimated by introducing a cost attribute from the perspective of the members of mandatory health insurance in Switzerland, i.e., using as a payment vehicle (or "cost attribute") the extra premium in exchange for a new intervention added to the package of services covered by OKP. The attributes tested further included clinical effectiveness (improvements of life expectancy and – separately – health-related quality of life as a result from adding the new intervention, compared to existing treatment options), age of patients (to capture the "fair innings" perspective), prevalence of the disorder (or "rarity"), i.e., the number of persons benefitting from adding access to the new intervention. Framing effects were assessed for the rarity and for the cost attribute by way of randomization of respondents to one out of four subgroups.

2. Health Related Quality of Life (HRQoL) and Capability Approach

Capability approach



One of the objectives of economic evaluations is the assessment of value. In conventional health economic practice, the value of new health technologies is assessed with a variety of different methodologies. The theoretical underpinnings of these methodologies are mostly based in welfarist and extra-welfarist traditions, which essentially focus on the measurement of utility as an account of value.

However, this focus on utility has been criticized as being too narrow by proponents of the capability approach. By evaluating utility—understood as the value elicited from what people have, who they are or what they do—important information on what people can have, can be or can do is missed. Imagine two persons who are hungry, the first person is fasting, while the second person is starving because of a famine. Even though both persons are hungry, it is clear that the person who is fasting has a better life than the person who is starving due to a famine. The person who fasts chooses to be hungry, while the starving person has no choice but be hungry.

Proponents of the capability approach thus argue that the evaluative scope should focus on measuring the freedom or opportunity of people to be, have or do. One of the assumptions is then, that an increase in freedom or opportunity leads to an increase in wellbeing. However, several issues do exist. First, it is unclear what kind of freedom a capability is. Second, it is unclear under which conditions an increase in freedom is related to an increase in wellbeing, given that research has shown that too much choice can in fact be stressful.

Against this background, this project tries to understand how freedom and wellbeing might be related to each other. By using a precise definition of what kind of freedom a capability is, an initial description of the dynamics between capability and wellbeing is created.


Multi-instrument comparison (MIC) study



Economic evaluation of medical interventions often relies on cost-effectiveness analyses, which report incremental cost per quality-adjusted life year (QALY) gained. Then, decreasing cost per QALY is interpreted as an indicator of increasing social desirability. In order to enable the calculation of QALYs and QALY gains, health-related quality of life (HRQoL) needs to be measured on a cardinal scale by a validated preference based generic instrument.

The MIC Study was designed by a team of health economists at the Monash University in Melbourne under the lead of Professor Jeff Richardson. It was conceived as an international research project in Australia, North America (Canada and USA), United Kingdom, Norway, and Germany, to explore the relative performance of and differences between the major generic instruments used to transform measurements of HRQoL into utility scores. Professor Schlander acted as Principal Investigator for the German arm of the study.

In order to pursue evaluations of the unique German dataset (comprising answers of 1,269 respondents), we are currently in the process examining cross-walks between the generic multi-attribute utility theory-based instruments (MAUIs), and mapping of disease-specific instruments on MAUI, all based on the preferences of German respondents.

Additionally, the Division is exploring the validity and sensitivity of the major MAUIs to variation in the quality of life measured by cancer-specific instruments. The aim is to examine the sensitivity of the general MAUIs scores to changes in the cancer-specific health-related quality of life instruments (such as FACT-G and the QLQ-C30), and whether particular dimensions of the general instrument are more sensitive.

3. Value and Benchmarks

Quantification of value of statistical life (VSLY)



The economic evaluation of medical interventions—for example, in the context of Health Technology Assessments (HTAs)—almost always implies some sort of (informal or formal) cost benefit analysis. At the heart of conventional health economic evaluations is a comparison of incremental costs and benefits. Essential dimensions of health-related benefits are length and quality of life.

There is, however, far-reaching uncertainty as to the appropriate anchor value of a statistical life year (VSLY). In the absence of a valid VSLY, a central point of reference is missing for most of the commonly used types of cost benefit analysis. Ideally, any benchmark for the VSLY—that might be also of interest to health care policy-makers—should be supported by empirical data capturing the preferences of the population in question.

Against this background, a systematic analysis of the relevant economic literature has been done, enabling a consolidated review of the contribution of empirical economic studies to our understanding of the VSLY and its drivers.

Selected Publications

J. J. Caro, J.E. Brazier, J. Karnon, P. Kolominsky-Rabas, A. J. McGuire, E. Nord, M. Schlander:
Determining value in Health Technology Assessment: Stay the course or tack away?
PharmacoEconomics, (2019) 37(3) 293-299.
DOI: 10.1007/s40273-018-0742-2.

J. Richardson, M. Schlander:
Health Technology Assessment (HTA) and economic evaluation: efficiency or fairness first.
Journal of Market Access & Health Policy, (2019) 7(1) 1-12.
DOI: 10.1080/20016689.2018.1557981.

R. Schaefer, M. Schlander:
Is the National Institute for Health and Care Excellence (NICE) in England more ´innovation-friendly´ than the Federal Joint Committee (GBA) in Germany?
Expert Review of Pharmacoeconomics & Outcomes Research, in press (2018).
DOI: 10.1080/14737167.2019.1559732

M.-J. Linton, P. M. Mitchell, H. Al-Janabi, M. Schlander, J. Richardson, A. Iezzi, J. Ubels, J. Coast:
Comparing the German translation of the ICECAP-A capability wellbeing measure to the original English version: Psychometric properties across healthy samples and seven health condition groups.
Applied Research in Quality of Life, in press (2018).
DOI: 1-23. 10.1007/s11482-018-9681-5.

M. Schlander:
Woran bemisst sich Effizienz im Gesundheitswesen? Zur Klärung fachwissenschaftlicher Begriffe und Kriterien.
Amos International, (2017) 11(1) 22-31.

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