Economische evaluaties en de zorgkosten van levensverlenging

Inleiding: Als iemand dankzij een preventieve of curatieve interventie langer leeft is het zeer waarschijnlijk dat deze persoon in zijn of haar extra levensjaren medische zorg consumeert. Neem als voorbeeld Jan die op 60-jarige leeftijd een succesvolle harttransplantatie heeft ondergaan. Dankzij de harttransplantatie sterft Jan niet in zijn 60ste levensjaar maar in zijn 75ste levensjaar en in deze 15 extra levensjaren zal Jan medische zorg consumeren. Deze medische zorg in gewonnen levensjaren wordt in de vakliteratuur vaak aangeduid met de term ‘indirecte medische kosten’. In een binnenkort te verschijnen artikel in het blad Health Economics hebben we gepoogd de theoretische discussie rondom indirecte medische kosten in het licht te zetten van de empirische literatuur rondom de kosten van vergrijzing en de huidige praktijk van economische evaluaties. In dit stuk wordt alvast een voorproefje op dat artikel gegeven

Health outcomes in Bulgaria:Simulated effects of obesogenic environmental changes in adulthood versus childhood

Objective: Bulgarian government efforts to tackle obesity are focused mainly on guidelines affecting children. However, it is unclear whether targeting children for obesity-related health policies yields better long-term health outcomes as opposed to changing the risk of obesity in adulthood. This study aims to evaluate where policy efforts should be directed to alleviate the health burden associated with obesity. Methods: We compare the impact on population health of two simulated scenarios when (a) the prevalence of obesity upon entering adulthood is lowered; (b) the risk of getting an unhealthy weight as an adult is reduced. Additionally, we run (c) combinations of the two and (d) childhood obesity prevention on the one hand, and worsening (increasing) obesity incidence later in adulthood on the other. Results: Our findings show that obesogenic environmental changes throughout adulthood have a stronger effect on life expectancy (LE), diabetes-free life expectancy (DFLE) and type 2 diabetes prevalence outcomes compared to lowering the proportion of individuals with obesity during adolescence. Nevertheless, a sizable reduction in the number of young adults with unhealthy weight has the potential to recover years of LE/DFLE that would be lost if the risk of obesity in adulthood would continue to grow in time. Conclusions: The two types of policies' (a-b) effects are not equivalent in strength and the best way forward is dependent on future obesity incidence trends.</p

The impact of different perspectives on the cost-effectiveness of remote patient monitoring for patients with heart failure in different European countries

Background and objective: Heart failure (HF) is a complex clinical syndrome with high mortality and hospitalization rates. Non-invasive remote patient monitoring (RPM) interventions have the potential to prevent disease worsening. However, the long-term cost-effectiveness of RPM remains unclear. This study aimed to assess the cost-effectiveness of RPM in the Netherlands (NL), the United Kingdom (UK), and Germany (DE) highlighting the differences between cost-effectiveness from a societal and healthcare perspective. Methods: We developed a Markov model with a lifetime horizon to assess the cost-effectiveness of RPM compared with usual care. We included HF-related hospitalization and non-hospitalization costs, intervention costs, other medical costs, informal care costs, and costs of non-medical consumption. A probabilistic sensitivity analysis and scenario analyses were performed. Results: RPM led to reductions in HF-related hospitalization costs, but total lifetime costs were higher in all three countries compared to usual care. The estimated incremental cost-effectiveness ratios (ICERs), from a societal perspective, were €27,921, €32,263, and €35,258 in NL, UK, and DE respectively. The lower ICER in the Netherlands was mainly explained by lower costs of non-medical consumption and HF-related costs outside of the hospital. ICERs, from a healthcare perspective, were €12,977, €11,432, and €11,546 in NL, the UK, and DE, respectively. The ICER was most sensitive to the effectiveness of RPM and utility values. Conclusions: This study demonstrates that RPM for HF can be cost-effective from both healthcare and societal perspective. Including costs of living longer, such as informal care and non-medical consumption during life years gained, increased the ICER.</p

Quantifying income inequality in years of life lost to COVID-19:a prediction model approach using Dutch administrative data

Background: Low socioeconomic status and underlying health increase the risk of fatal outcomes from COVID-19, resulting in more years of life lost (YLL) among the poor. However, using standard life expectancy overestimates YLL to COVID-19. We aimed to quantify YLL associated with COVID-19 deaths by sex and income quartile, while accounting for the impact of individual-level pre-existing health on remaining life expectancy for all Dutch adults aged 50þ. Methods: Extensive administrative data were used to model probability of dying within the year for the entire 50þ population in 2019, considering age, sex, disposable income and health care use (n ¼ 6 885 958). The model is used to predict mortality probabilities for those who died of COVID-19 (had they not died) in 2020. Combining these probabilities in life tables, we estimated YLL by sex and income quartile. The estimates are compared with YLL based on standard life expectancy and income-stratified life expectancy. Results: Using standard life expectancy results in 167 315 YLL (8.4 YLL per death) which is comparable to estimates using income-stratified life tables (167 916 YLL with 8.2 YLL per death). Considering pre-existing health and income, YLL decreased to 100 743, with 40% of years lost in the poorest income quartile (5.0 YLL per death). Despite individuals in the poorest quartile dying at younger ages, there were minimal differences in average YLL per COVID-19 death compared with the richest quartile. Conclusions: Accounting for prior health significantly affects estimates of YLL due to COVID-19. However, inequality in YLL at the population level is primarily driven by higher COVID-19 deaths among the poor. To reduce income inequality in the health burden of future pandemics, policies should focus on limiting structural differences in underlying health and exposure of lower income groups.</p

Quantifying income inequality in years of life lost to COVID-19:a prediction model approach using Dutch administrative data

Background: Low socioeconomic status and underlying health increase the risk of fatal outcomes from COVID-19, resulting in more years of life lost (YLL) among the poor. However, using standard life expectancy overestimates YLL to COVID-19. We aimed to quantify YLL associated with COVID-19 deaths by sex and income quartile, while accounting for the impact of individual-level pre-existing health on remaining life expectancy for all Dutch adults aged 50þ. Methods: Extensive administrative data were used to model probability of dying within the year for the entire 50þ population in 2019, considering age, sex, disposable income and health care use (n ¼ 6 885 958). The model is used to predict mortality probabilities for those who died of COVID-19 (had they not died) in 2020. Combining these probabilities in life tables, we estimated YLL by sex and income quartile. The estimates are compared with YLL based on standard life expectancy and income-stratified life expectancy. Results: Using standard life expectancy results in 167 315 YLL (8.4 YLL per death) which is comparable to estimates using income-stratified life tables (167 916 YLL with 8.2 YLL per death). Considering pre-existing health and income, YLL decreased to 100 743, with 40% of years lost in the poorest income quartile (5.0 YLL per death). Despite individuals in the poorest quartile dying at younger ages, there were minimal differences in average YLL per COVID-19 death compared with the richest quartile. Conclusions: Accounting for prior health significantly affects estimates of YLL due to COVID-19. However, inequality in YLL at the population level is primarily driven by higher COVID-19 deaths among the poor. To reduce income inequality in the health burden of future pandemics, policies should focus on limiting structural differences in underlying health and exposure of lower income groups.</p

Cured today, ill tomorrow: a method for including future unrelated medical costs in economic evaluation in England and Wales

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