Applied Health Economics and Health Policy最新文献

There has been increasing interest in including carers’ health-related qualify of life (HRQoL) in decision models, but currently there is no best practice guidance as to how to do so. Models thus far have typically assumed that carers’ HRQoL can be predicted from patient health states, as we illustrate with three examples of disease-modifying treatments. However, this approach limits the mechanisms that influence carers’ HRQoL solely to patient health and may not accurately reflect carers’ outcomes. In this article, we identify and discuss challenges associated with modelling intervention effects on carers’ HRQoL: attaching carer utilities to patient disease states, the size of the caring network, aggregation of carer and patient HRQoL, patient death, and modelling longer-term carer HRQoL. We review and critique potential alternatives to modelling carers’ HRQoL in decision models: trial-based analyses, qualitative consideration, cost-consequence analysis, and multicriteria decision analysis, noting that each of these also has its own challenges. We provide a framework of issues to consider when modelling carers’ HRQoL and suggest how these can be addressed in current practice and future research.

Background

Health interventions contribute to the production of greenhouse gas emissions. Thus, reducing carbon footprint is essential in supporting the UK National Health Service (NHS) pathway to net zero. This study explores the approach in which carbon footprint can be included when applying Health Technology Assessment (HTA) modelling using obesity intervention in the United Kingdom (UK) as a case study.

Methods

Using decision analytic modelling, we conducted an HTA incorporating the impacts of obesity-related treatment decisions on UK carbon emissions. A cohort Markov model was used to track the emissions of the UK population after receiving one of two obesity treatments: semaglutide and bariatric surgery.

Results

This study introduced two new carbon measurement tools that may be useful for future policymaking, incremental carbon footprint effectiveness ratio (ICFER) and incremental carbon footprint cost ratio (ICFCR), which made it possible to assess the emission impacts of proposed health policies. Using the obesity intervention case study, we found that both treatments have an incremental cost-effectiveness ratio (ICER) of < £20,000 per quality-adjusted life-years (QALYs) gained. This is below the UK threshold, indicating that these are cost-effective treatments for obesity, but could increase the NHS carbon footprint. However, it could reduce the overall UK societal carbon footprint by reducing the number of people with obesity. The ICFCR shows a reduction of 1.13–4.51 kgCO₂e (kilogram of carbon dioxide equivalent) for every pound spent on obesity treatment.

Conclusion

This study illustrates a case study for estimating the effect of health policies on carbon emissions and provides a quantitative measure for obesity-related treatment decisions.

Objective

To assess the cost effectiveness of the second COVID-19 booster vaccination with different age groups.

Methods

We developed a decision-analytic Susceptible-Exposed-Infected-Recovered (SEIR)-Markov model by five age groups (0–4 years, 5–11 years 12–17 years, 18–49 years, and 50+ years) and calibrated the model by actual mortality in each age group in the USA. We conducted five scenarios to evaluate the cost effectiveness of the second booster strategy and incremental benefits if the strategy would expand to 18–49 years and 12–17 years, from a health care system perspective. The analysis was reported according to the Consolidated Health Economic Evaluation Reporting Standards 2022 statement.

Results

Implementing the second booster strategy for those aged ≥ 50 years cost $823 million but reduced direct medical costs by $1166 million, corresponding to a benefit-cost ratio of 1.42. Moreover, the strategy also resulted in a gain of 2596 quality-adjusted life-years (QALYs) during the 180-day evaluation period, indicating it was dominant. Further, vaccinating individuals aged 18–49 years with the second booster would result in an additional gain of $1592 million and 8790 QALYs. Similarly, expanding the vaccination to individuals aged 12–17 years would result in an additional gain of $16 million and 403 QALYs. However, if social interaction between all age groups was severed, vaccination expansion to ages 18–49 and 12–17 years would no longer be dominant but cost effective with an incremental cost-effectiveness ratio (ICER) of $37,572 and $26,705/QALY gained, respectively.

Conclusion

The second booster strategy was likely to be dominant in reducing the disease burden of the COVID-19 pandemic. Expanding the second booster strategy to ages 18–49 and 12–17 years would remain dominant due to their social contacts with the older age group.

Background

Atrial fibrillation (AF) is a severe epidemiological and public health concern among the elderly population worldwide, with substantial economic and social burdens. Economic evaluations can play an essential role in optimizing the utilization of scarce resources. In recent years, the number of economic evaluation studies related to AF has increased due to the rising number of AF patients, the continuous updating of clinical data, and the emergence of real-world evidence. However, there are still deficiencies in model settings and parameter sources in relevant studies.

Objective

This study aims to review the existing economic evaluations of novel oral anticoagulants (NOACs) in patients with AF and summarize the evidence and methods applied.

Methods

A comprehensive and systematic search was conducted on electronic databases, including PubMed, Embase, Web of Science (WOS), and The Cochrane Library, from the date of database creation to November 2022. The reporting quality of included literature was assessed using the Consolidated Health Economic Evaluation Reporting Standards 2022 (CHEERS 2022) statement.

Results

A total of 102 studies were included in the review, with 200 comparisons between NOACs and vitamin K antagonists (VKAs), as well as 58 comparisons between different NOACs. The healthcare sector and payer perspectives were the most common, and accordingly, the majority of the evaluations considered only direct medical costs. Most studies used Markov cohort models with the number of health states ranging from 4 to 29. Of included studies, 80 (78%) considered event recurrence and complications, and 78 (76%) considered discontinuation and second-line therapy. All of the studies applied uncertainty analysis to explore the robustness of the results. Of all 200 NOACs-VKAs comparisons, 149 (75%) showed that NOACs were more cost-effective; this proportion was 84% (139 out of 165) in high-income countries but decreased to 29% (10 out of 35) in middle- and low-income countries. Most (82%) of the 28 items in the CHEERS 2022 checklist were elucidated in the majority of included studies. A minority (only 39%) of included studies demonstrated high reporting quality.

Conclusion

NOACs may be more cost-effective than VKAs in patients with AF, but this conclusion applies to high-income countries, whereas VKAs may be more cost-effective in middle- and low-income countries. The reporting quality of included studies was variable, and certain methodological issues were presented. This study highlights the economic evaluation methodology of NOACs in patients with AF and provides recommendations for modeling methods and future studies.

Objective

We compared two generic, preference-based health-outcome measures: the novel patient-centered Château-Santé Base (CS-Base), entailing a multi-attribute preference response framework, and the widely used EQ-5D-5L, regarding effects of different measurement frameworks and different descriptive systems.

Methods

We conducted a cross-sectional study using a random sample of patients (3019 reached, 1988 included) in the USA with various health conditions. The CS-Base (12 attributes, each with four levels), EQ-5D-5L and the 5D-4L (an ad hoc, multi-attribute preference response-based measure that includes five attributes similar to the EQ-5D-5L, but with four levels) were used as health-outcome measures. We compared the proportions of problems reported on health attributes, statistical robustness and face validity of coefficients, attribute importance, differentiation between health states based on health-state values obtained with these measures, and user experience.

Results

All the CS-Base and 5D-4L coefficients had logical orders and significant differences from the reference level (p < 0.001). Substantial differences were observed in the CS-Base and 5D-4L coefficients between all levels on all attributes, while subtle differences were seen in those of the EQ-5D-5L. Attribute importance of usual (daily) activities were lowest or second lowest in all the three health-outcome measures. Attributes with the highest importance in the CS-Base, 5D-4L, and EQ-5D-5L were respectively mobility, anxiety/depression, and pain/discomfort. Four attributes are similar between the CS-Base and EQ-5D-5L, eight are exclusive to CS-Base. Of the eight, vision and hearing had the highest importance. Health-state values showed a smoother distribution with minimal discontinuity in the CS-Base and EQ-5D-5L than in the 5D-4L. In user experience evaluation, both CS-Base and the 5D-4L showed mean scores above 50 (indicating positive evaluation) in terms of the description of health and ease of understanding.

Conclusions

This study demonstrated that CS-Base and 5D-4L, which are grounded in the multi-attribute preference response framework, produced statistically robust coefficients, with better face validity than those for the EQ-5D-5L. CS-Base and the EQ-5D-5L outperformed the 5D-4L in differentiating between health states. Notwithstanding differences in content, measurement frameworks, and estimated coefficients, the computed health-state values were similar between CS-Base and EQ-5D-5L.

There is currently deep uncertainty about the clinical benefits and cost effectiveness of highly specialised technologies (HSTs), like gene and cell therapies. These treatments are novel, typically have high upfront costs, the patient populations are small and heterogenous, there is minimal information on their long-term safety and effectiveness, and data are limited and often of poor quality. With the increasing number of these technologies and their high cost burden on governments and health care providers, policy makers are currently walking a decision tightrope. On the one hand, an unfavourable funding decision could potentially limit patient access to life-saving treatments, while on the other, a favourable decision could result in unsustainable budget impacts and perhaps poorer patient health outcomes. Health technology assessment (HTA) is meant to determine the value of a health technology in order to promote an equitable, efficient, and high-quality health system. However, standard HTA processes have failed to mitigate the deep uncertainties associated with these technologies. In this paper, we propose a Living HTA framework to address these challenges. This framework includes a one-off process for making explicit the societal values associated with HSTs. These would inform the decision-making approach, data collection and the development of disease-specific reference models to be used by industry sponsors as the basis for their submissions for public funding. Coverage with an evidence development mechanism is also proposed by which data can be collected in real time to update the reference model on a rolling basis, thereby allowing re-assessment of the clinical and cost effectiveness of individual HSTs. The HTA would be ‘live’ until the results indicate there is sufficient certainty for the funding decision to be confirmed, the price changed or the funding removed.

Background and Objective

In pursuit of universal health coverage, India has launched the world’s largest government-sponsored health insurance scheme, Pradhan Mantri Jan Arogya Yojana (PM-JAY) in 2018. This study aims to provide a holistic review of the scheme’s impact since its inception.

Methods

We reviewed studies (based on interviews or surveys) published from September 2018 to January 2023, which were retrieved from PubMed, Web of Science, and Scopus database. The main outcomes studied were: (1) awareness; (2) utilization of scheme; (3) experiences; (4) financial protection; and (5) challenges encountered by both beneficiaries and healthcare providers.

Results

A total of 18 studies conducted across 14 states and union territories of India were reviewed. The findings revealed that although PM-JAY has become a familiar name, there remains a low level of awareness regarding various facets of the scheme such as benefits entitled, hospitals empanelled, and services covered. The scheme is benefitting the poor and vulnerable population to access healthcare services that were previously unaffordable to them. However, financial protection provided by the scheme exhibited mixed results. Several challenges were identified, including continued spending by beneficiaries on drugs and diagnostic tests, delays in issuance of beneficiary cards, and co-payments demanded by healthcare providers. Additionally, private hospitals expressed dissatisfaction with low health package rates and delays in claims reimbursement.

Conclusions

Concerted efforts such as population-wide dissemination of clear and complete knowledge of the scheme, providing training to healthcare providers, addressing infrastructural gaps and concerns of healthcare providers, and ensuring appropriate stewardship are imperative to achieve the desired objectives of the scheme in the long-run.

Objective

We explored the monetary value of the end-of-life (EoL) health gains, that is, the value of a life-year (VOLY) gained at the end of a patient’s life in Croatia. We tested whether the nature of the illness under valuation (cancer and/or rare disease) is a factor in the valuation of EoL-VOLYs. The aim was for our results to contribute to the health and longevity valuation literature and more particularly to the debate on the appropriate cost-effectiveness threshold for EoL treatments as well as to provide input into the debate on the justifiability of a cancer and/or a rare disease premium when evaluating therapies.

Methods

A contingent valuation was conducted in an online survey using a representative sample of the Croatian population (n = 1500) to calculate the willingness to pay for gains in the remaining life expectancy at the EoL, from the social-inclusive-individual perspective, using payment scales and an open-ended payment vehicle. Our approach mimics the actual decision-making problem of deciding whether to reimburse therapies targeting EoL conditions such as metastatic cancer whose main purpose is to extend life (and not add quality to life).

Results

Average EoL-VOLY across all scenarios was estimated at €67,000 (median €40,000). In scenarios that offered respondents 1 full year of life extension, EoL-VOLY was estimated at €33,000 (median €22,000). Our results show that the type of illness is irrelevant for EoL-VOLY evaluations.

Conclusions

The pressure to reimburse expensive therapies targeting EoL conditions will continue to increase. Delivering “value for money” in healthcare, both in countries with relatively higher and lower budget restrictions, requires the valuation of different types of health gains, which should, in turn, affect our ability to evaluate their cost effectiveness.