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Objectives In many countries, future unrelated medical costs occurring during life-years gained are excluded from economic evaluation, and benefits of unrelated medical care are implicitly included, leading to life-extending interventions being disproportionately favored over quality of life-improving interventions. This article provides a standardized framework for the inclusion of future unrelated medical costs and demonstrates how this framework can be applied in England and Wales. Methods Data sources are combined to construct estimates of per-capita National Health Service spending by age, sex, and time to death, and a framework is developed for adjusting these estimates for costs of related diseases. Using survival curves from 3 empirical examples illustrates how our estimates for unrelated National Health Service spending can be used to include unrelated medical costs in cost-effectiveness analysis and the impact depending on age, life-years gained, and baseline costs of the target group. Results Our results show that including future unrelated medical costs is feasible and standardizable. Empirical examples show that this inclusion leads to an increase in the ICER of between 7% and 13%. Conclusions This article contributes to the methodology debate over unrelated costs and how to systematically include them in economic evaluation. Results show that it is both important and possible to include future unrelated medical costs.

Recently, due to the corona virus outbreak, pandemics and their effects have been at the forefront of the research agenda. However, estimates of the perceived value of early warning systems (EWSs) for identifying, containing, and mitigating outbreaks remain scarce. This paper aims to show how potential health gains due to an international EWS might be valued. This paper reports on a study into willingness to pay (WTP) in six European countries for health gains due to an EWS. The context in which health is gained, those affected, and the reduction in risk of contracting the disease generated by the EWS are varied across seven scenarios. Using linear regression, we analyse this ‘augmented’ willingness to pay for a QALY (WTP-Q) for each of the scenarios, where ‘augmented’ refers to the possible inclusion of context specific elements of value, such as feelings of safety. An initial WTP-Q estimate for the basic scenario is €17,400. This can be interpreted as a threshold for investment per QALY into an EWS. Overall, WTP estimates move in the expected directions (e.g. higher risk reduction leads to higher WTP). However, changes in respondents’ WTP for reductions in risk were not proportional to the magnitude of the change in risk reduction. This study provided estimates of the monetary value of health gains in the context of a pandemic under seven scenarios which differ in terms of outcome, risk reduction and those affected. It also highlights the importance of future research into optimal ways of eliciting thresholds for investments in public health interventions.

Objectives: A consensus has been reached in The Netherlands that all future medical costs should be included in economic evaluations. Furthermore, internationally, there is the recognition that in countries that adopt a societal perspective estimates of future nonmedical consumption are relevant for decision makers as much as production gains are. The aims of this paper are twofold: (1) to update the tool Practical Application to Include Future Disease Costs (PAID 1.1), based on 2013 data, for the estimation of future unrelated medical costs and introduce future nonmedical consumption costs, further standardizing and facilitating the inclusion of future costs; and (2) to demonstrate how to use the tool in practice, showing the impact of including future unrelated medical costs and future nonmedical consumption in a case-study where a life is hypothetically saved at different ages and 2 additional cases where published studies are updated by including future costs. Methods: Using the latest published cost of illness data from the year 2017, we model future unrelated medical costs as a function of age, sex, and time to death, which varies per disease. The Household Survey from Centraal Bureau Statistiek is used to estimate future nonmedical consumption by age. Results: The updated incremental cost-effectiveness ratios (ICERs) from the case studies show that including future costs can have a substantial effect on the ICER, possibly affecting choices made by decision makers. Conclusion: This article improves upon previous work and provides the first tool for the inclusion of future nonmedical consumption in The Netherlands.

Early warning systems for infectious diseases and foodborne outbreaks are designed with the aim of increasing the health safety of citizens. As a first step to determine whether investing in such a system offers value for money, this study used contingent valuation to estimate people’s willingness to pay for such an early warning system in six European countries. The contingent valuation experiment was conducted through online questionnaires administered in February to March 2018 to cross-sectional, representative samples in the UK, Denmark, Germany, Hungary, Italy, and The Netherlands, yielding a total sample size of 3140. Mean willingness to pay for an early warning system was €21.80 (median €10.00) per household per month. Pooled regression results indicate that willingness to pay increased with household income and risk aversion, while they decreased with age. Overall, our results indicate that approximately 80–90% of people would be willing to pay for an increase in health safety in the form of an early warning system for infectious diseases and food-borne outbreaks. However, our results have to be interpreted in light of the usual drawbacks of willingness to pay experiments. Electronic supplementary material The online version of this article (10.1007/s10198-020-01171-2) contains supplementary material, which is available to authorized users.

Purpose The pressure on healthcare budgets remains high, partially due to the ageing population. Economic evaluation can be a helpful tool to inform resource allocation in publicly financed systems. Such evaluations frequently use health-related outcome measures. However, in areas such as care of older people, improving health outcomes is not necessarily the main focus of care interventions and broader outcome measures, including outcomes for those providing informal care, may be preferred when evaluating such interventions. This paper validates a recently introduced well-being measure, the ICECAP-O, in a population of informal carers for people with dementia from eight European countries. Methods Convergent and discriminant validity tests were performed to validate the ICECAP-O using data obtained in a sample of 451 respondents from Germany, Ireland, Italy, the Netherlands, Norway, Portugal, Sweden and the UK. These respondents completed a number of standardized questionnaires within the framework of the Actifcare project. Results The ICECAP-O performed well among informal carers, in terms of both convergent and discriminant validity. In the multivariate analysis, it was found to be significantly associated with the age of the person with dementia, EQ-5D-5L health problem index of the person with dementia, carer–patient relationship, care recipient CDR, carer LSNS Score, the PAI score, and Perseverance Time. Conclusion The ICECAP-O appears to be a valid measure of well-being in informal carers for people with dementia. The ICECAP-O may therefore be useful as an outcome measure in economic evaluations of interventions aimed at such informal carers, when these aim to improve well-being beyond health.

Traditionally, threshold levels of cost‐effectiveness have been derived from willingness‐to‐pay studies, indicating the consumption value of health (v‐thresholds). However, it has been argued that v‐thresholds need to be supplemented by so‐called k‐thresholds, which are based on the marginal returns to health care. The objective of this research is to estimate a k‐threshold based on the marginal returns to cardiovascular disease (CVD) hospital care in the Netherlands. To estimate a k‐threshold for hospital care on CVD, we proceed in two steps: First, we estimate the impact of hospital spending on mortality using a Bayesian regression modelling framework, using data on CVD mortality and CVD hospital spending by age and gender for the period 1994–2010. Second, we use life tables in combination with quality of life data to convert these estimates into a k‐threshold expressed in euros per quality‐adjusted life year gained. Our base case estimate resulted in an estimate of 41,000 per quality‐adjusted life year gained. In our sensitivity analyses, we illustrated how the incorporation of prior evidence into the estimation pushes estimates downwards. We conclude that our base case estimate of the k‐threshold may serve as a benchmark value for decision making in the Netherlands as well as for future research regarding k‐thresholds.